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Q1:Module 6: Homework Assignment 30 pts. Respond to the prompt(s) for each item below using complete sentences and clear writing. You may single-space your work. A cover page or page numbers are not required. Cite and reference only where indicated unless you utilize outside sources in a response. Please do item 1,2,3 only Return to the assignment page when you are ready to submit your assignment. Collaboration on this assignment is NOT allowed. Your work must be your own. Item 1 (2 pts.) What do p-values and effect sizes tell us about the significance of our results? Be sure to comment on any similarities or differences between the two. Item 2 (5 pts.) Explain the relationships between ... A. Sample size and Confidence intervals (1 pt.) B. Power and Effect size (1 pt.) C. Sample size and Power (1 pt.) D. Power and Type II Error (1 pt.) E. Alpha and Power (1 pt.) Item 3 (7 pts.) Use the following scenario to respond to parts A - D. Nancy compares the effectiveness of two forms of psychotherapy against a control group (no therapy) for obsessive compulsive disorder. The IV and DV are listed below: IV = Therapy Condition (Therapy A, Therapy B, No Therapy) DV = Effectiveness Score (pre-to-post reduction in symptoms) Nancy sets the hypotheses as follows: H0 = There are no differences among the mean effectiveness scores of groups. Ha = There are statistically significant differences among the mean effectiveness scores of groups. A. Explain what it would mean in this scenario if Nancy were to commit a Type I error. (2 pts.) B. Explain what it would mean in this scenario if Nancy were to commit a Type II error. (2 pts.) C. If the results of the data analysis support the alternative hypothesis, what was Nancy's decision about the null hypothesis? (1 pt.) D. If the results of the data analysis support the alternative hypothesis, is the following statement appropriate? Explain. (2 pts.) Therapy A is more effective than Therapy B which is more effective than having no treatment. USE THE FOLLOWING SCENARIO TO ANSWER ITEMS 4 AND 5: Jack wants to investigate the mean differences between middle-aged adults and older adults on a quantitative measure of life satisfaction (0 - 7 scale). Jack expects that life satisfaction will differ between the age groups. Item 4 (6 pts.) A. What is the more appropriate statistical test for him to use and why? (2 pts) B. Explain power within the context of this study. Be sure to reference null and alternative hypotheses in your explanation. (4 pts.) Item 5 (10 pts.) After running the appropriate statistical tests, Jack finds that life satisfaction was in the older adults (M = 4.9, SD = 1.2) than in middle-aged adults (M = 4.1, SD = 1.8), t(58) = 2.03, p = . 047, 95% CI [0.01, 1.59], d = . 52. A. From these statistical results, what conclusions can Jack make? Comment on whether there are statistically significant differences between the groups and how you know. (2 pts) B. What should Jack decide about the hypotheses? State the decision and explain what the decision means in the context of this study. (2 pts.) C. What does the "t(58) = 2.03" tell us? (2 pts.) D. What can we conclude from the confidence interval within the context of this study? (2 pts) E. What does the effect size tell us within the context of this study? (2 pts)/nModule 6: Homework Assignment 30 pts. Respond to the prompt(s) for each item below using complete sentences and clear writing. You may single-space your work. A cover page or page numbers are not required. Cite and reference only where indicated unless you utilize outside sources in a response. The weekly homework assignment requires very thorough and detailed answers. These are not 1-2 sentence responses. Please take your time and be sure to elaborate on all your answers. Min word count:500 APA format mandatory Return to the assignment page when you are ready to submit your assignment. Collaboration on this assignment is NOT allowed. Your work must be your own. Item 1 Item 2 Item 3See Answer
Q2:Students are required to select a research article or an academic project paper of research interests. Read the selected article/paper and provide the summary of the reading. A good paper summary should include the following components: 1. An overview of the article at the beginning, including the title and author names. 2. Describe the main topic, background/introduction of the paper, condense the main points in your own words. 3. State the research aims and/or hypothesis. Usually, the research aims are described at the last part of the background/introduction or at the beginning of the methods section. Research aims will run through the entire research article. 4. Summarize the study design and research methods. For example: describe the study method (randomized clinical trial, prospective cohort study or case-control study, etc); participants recruited in the study; inclusion and exclusion criteria; sample size; explain how measurements were made and what calculations were performed; what statistical tests were done. 5. State the most important results in details. Are the findings supported by previous research? What are the limitations of the study? 6. One or two sentences' summary of the conclusion. The summary should be about within 2 pages (double space with a 12-font size). Instructions: Need to answer all the questions above Plagiarism free Solutions generated from any AI platform is strictly Prohibited Solution to be formatted in APA and use appropriate references with in-text citations/nPatient Education and Counseling 86 (2012) 233-238 Contents lists available at ScienceDirect Patient Education and Counseling Patient Education and Counseling journal homepage: www.elsevier.com/locate/pateducou Intervention Relationship between improvements in heart failure patient disease specific knowledge and clinical events as part of a randomized controlled trial Naga V.A. Kommuria, Monica L. Johnson b, Todd M. Koelling b,* ª Department of Internal Medicine, Wayne State University, Detroit, USA b Department of Internal Medicine, University of Michigan, Ann Arbor, USA ARTICLE INFO Article history: Received 1 December 2010 Received in revised form 2 May 2011 Accepted 9 May 2011 Keywords: Heart failure Patient education Hospitalization Knowledge Outcomes ABSTRACT Objective: To examine the changes in performance on heart failure knowledge assessments administered before and after discharge education. Methods: We conducted a randomized controlled trial comparing the effects of a 1-h, one-on-one teaching session with a nurse educator to the standard discharge process in patients with systolic heart failure. Patients completed a 30 point heart failure knowledge questionnaire (HFKQ) prior to and 3 months after the education intervention. Results: Patients randomized to the nurse education intervention (n = 113) demonstrated significantly higher total HFKQ score increases compared to patients receiving the standard discharge process (n = 114) (median, IQR 1, 0 to 4 vs 0, -2 to 2, p = 0.007). Patients experiencing death or rehospitalization in the subsequent 6 months were found to have significantly lower HFKQ scores (10, 7 to 12 vs 11, 8 to 13, p = 0.002) compared to patients without a clinical event. Conclusion: Heart failure nurse education at the time of hospital discharge results in improved patient knowledge and reduced risk of readmission. Practice implications: Health care personnel should encourage education sessions for heart failure patients. Resources possibly need to be allocated for nurse led education sessions in heart failure patients as it improves outcomes and knowledge. @ 2011 Elsevier Ireland Ltd. All rights reserved. 1. Introduction Patient education has been recognized to play a critical role in the care of patients with heart failure [1,2]. Multiple studies have evaluated the effects of heart failure patient discharge education combined with various post-discharge support programs [3-16]. These studies have demonstrated improved clinical outcomes, reductions in hospitalizations, and reduced costs compared to control groups. Whether these benefits are due to the additional disease specific education, the post- discharge support programs, or a combination of the two is difficult to understand. Furthermore, because these prior studies have not assessed heart failure patient knowledge concurrently with the educational interventions, establishing a relationship between improvements in knowledge and improvements in clinical outcomes has not been possible. Recently, we demonstrated that heart failure patient educa- tion delivered face-to-face by a nurse educator at the time of hospital discharge leads to lower rates of hospital readmission compared to patients receiving written materials as part of the standard discharge process [7]. Additionally, patients random- ized to receive the nurse educator delivered intervention were more likely to be following appropriate self-care behaviors [7]. Whether heart failure patient education leads to measurable changes in disease specific knowledge is not known. Further- more, it is not known whether potential improvements in heart failure patient knowledge are associated with clinical outcomes and/or self-care behaviors. If a significant relationship exists between improvements in heart failure knowledge and clinical outcomes, then it may be possible to improve the efficiency of educational efforts by identifying patients most likely to benefit from the intervention. To improve this understanding, we have examined changes in performance on heart failure knowledge assessments administered before and after discharge education administered as part of a randomized controlled trial. * Corresponding author at: Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, 1500 E. Medical Center Drive, CVC Room 2167, SPC 5853, Ann Arbor, MI 48109, USA. Tel .: +1 734 764 7440; fax: +1 734 615 3326. E-mail address: tkoellin@umich.edu (T.M. Koelling). 0738-3991/$ - see front matter @ 2011 Elsevier Ireland Ltd. All rights reserved. doi: 10.1016/j.pec.2011.05.019 Downloaded for Anonymous User (n/a) at Florida State University from ClinicalKey.com by Elsevier on March 02, 2022. For personal use only. No other uses without permission. Copyright @2022. Elsevier Inc. All rights reserved. ELSEVIER 234 N.V.A. Kommuri et al./ Patient Education and Counseling 86 (2012) 233-238 2. Methods 2.1. Subjects This study was performed at the University of Michigan Hospital and was approved by the Medical School Institutional Review Board. Study subjects were recruited from eligible candidates admitted to the hospital with a diagnosis of heart failure (International Classification of Diseases, 9th ed. [ICD9-CM] 402.1, 402.11, 402.91, 404.01, 404.91, or 428.x) and documented left ventricular systolic dysfunction (ejection fraction ≤ 0.40). For the current study, a total of 667 subjects were screened for enrollment into the study during the recruitment period. Of those screened 402 were excluded from enrollment and the remaining 265 patients were included in the study (Fig. 1). At the time of study enrollment, information regarding compliance with diet and medication was extracted from the medical records. The study coordinator reviewed the admission note, medical records and problem summary list for evidence of non compliance. 2.2. Study design Details about the patient recruitment, randomization process, education intervention and patient follow up are described in our previous papers [7,17]. Briefly, after obtaining informed consent, patients were randomized to receive usual care (standard discharge information) or usual care plus a 1-h long nurse educator delivered heart failure education program. The education session covered details about the basic principles of heart failure, role of dietary sodium, importance of limitation of fluid intake as well as the mechanisms of diuretics and the rationale for other pharmacotherapy. Specific instructions were given to limit the dietary sodium intake to 2000 mg or less and the daily fluid intake to 2000 ml or less. Furthermore, during the session patients were given information about the importance of daily weight monitor- ing, self care behaviors, compliance of medications, smoking cessation, avoiding non steroidal anti inflammatory drugs, limitation of alcohol intake and the measures to take when the symptoms are worse. The intervention group also received heart failure management guidelines written in layman's terms. 2.3. Heart failure knowledge questionnaire The HFKQ was developed by the study team and has not been previously described. The HFKQ was administered to the study population at baseline and 3 months after hospital discharge by the study coordinator. The specific questions included in the HFKQ may be reviewed in the Appendix. The HFKQ contains 30 questions No. Assessed for eligibility: 667 No. Excluded: 402 Refused to participate: 29 Other reasons: 373 Cardiac surgery workup: 80 Noncardiac life threatening illness: 62 Transplant evaluation: 48 Dementia/Psychiatric illness: 46 Unable to follow up by phone: 27 1 Creatinine > 3.5 mg/dl: 24 Long term care facility: 23 Aortic stenosis: 22 Discharged before enrollment: 18 Other research study: 8 Active infection: 8 Acute MI: 7 > No. Consented for study: 265 > No. Enrolled Control Group: 137 No. Enrolled Education Group: 128 No. Not tested in Control Group: 23 No. Not tested in Education Group: 15 Deceased prior to 3 mo FU: 11 Hospitalized at 3 mo FU: 7 Deceased prior to 3 mo FU: 6 Hospitalized at 3 mo FU: 5 Declined questionnaire: 4 < Declined questionnaire: 5 > No. Included at 3 month HFKQ No. Included at 3 month HFKQ testing in Control Group: 114 testing in Education Group: 113 Fig. 1. Patient screening and randomization assignment profile. Downloaded for Anonymous User (n/a) at Florida State University from ClinicalKey.com by Elsevier on March 02, 2022. For personal use only. No other uses without permission. Copyright @2022. Elsevier Inc. All rights reserved. 235 N.V.A. Kommuri et al./ Patient Education and Counseling 86 (2012) 233-238 in total, and requires approximately 10 min to complete. The first 15 questions of the HFKQ assess general HF disease knowledge, self-care management behaviors, and medications used in the treatment of heart failure with left ventricular systolic dysfunction. For the purposes of this paper, these questions have been designated as the disease management knowledge (DMK) ques- tions. The remaining 15 questions of the HFKQ assess patient knowledge of dietary recommendations in heart failure and specific sodium content of common foods. These questions have been designated as the dietary and sodium knowledge (DSK) questions. Scoring of the questionnaire assigned a value of 1 point for each correct answer. In addition to the HFKQ testing, enrolled patients completed a questionnaire regarding self-care practices at the time of enroll- ment, 30, 90 and 180 days after hospital discharge. These self-care practices entailed self reported adherence to daily weight monitoring, dietary sodium restriction, fluid restriction, avoidance of smoking tobacco products, having a plan for what to do for worsened symptoms and performance of exercise ≥3 times per week. In this study, we performed a comparison of the 3 month follow-up HFKQ scores with respect to compliance to each of the self-care measures. 2.4. Statistical analysis The primary endpoint of the study was the change in HFKQ score from baseline to the 3 month time point after hospital discharge. Changes in HFKQ scores for the patients randomized to receive nurse education (NE) and controls were compared using the non-parametric Mann-Whitney U test. Changes in HFKQ scores were also compared for patients with or without a clinical event during the 180 day follow-up period. Clinical events were defined as death or hospitalization within the 180 day follow up period. We performed a stepwise multivariable logistic regression analysis to understand the contributors for improvement in heart failure knowledge. Variables entered into the model included age greater than 70 years, gender, white race, duration of disease less than 3 months, no insurance, Medicaid insurance, Medicare insurance, adjusted gross income less than $45,000/year, educa- tion level achieved less than high school diploma and study group assignment. Forward stepwise regression was used to identify independent predictors of improved total HFKQ score. An additional multivariable regression was performed in the interest of understanding the mechanism of improved clinical outcomes in our study, using the technique of mediator analysis suggested by Mackinnon et al. [18] In this analysis, the clinical event, death or rehospitalization within 6 months was the dependent variable while the patient treatment assignment and total HFKQ score at 3 month follow up were entered as covariates. All analyses were performed with SPSS version 17.0 statistical software. A p value of <0.05 was considered statistically significant. Unless otherwise specified, data are expressed as median and interquartile range. 3. Results The comparisons of baseline characteristics for the control and education groups are shown in Table 1 and demonstrate that the two groups were similar with respect to age, sex, socioeconomic status, left ventricular ejection fraction, NYHA classification, clinical comorbidities and laboratory values. Patients in the education group were found to have higher blood pressure than controls. Table 2 shows that baseline knowledge was similar for the two groups. Patients in control group did not demonstrate any improvement in their knowledge (DSK, DMK, total score) at the 3 month follow-up. However, patients in the education group demonstrated a significant improvement in their DMK (<0.001) as well as in the total score (<0.001) during follow up. Neither the control group nor the education group demonstrated improve- ments in their DSK during the study (Table 2). Table 1 Baseline characteristics of study population. Control Education n=128 p value n=137 Age (years) 67 (57, 74) 67 (55, 76) 0.82 Female % 39 39 0.82 White % Education (% not finishing high school) Income ($ in thousands) Uninsured % 76 80 0.46 30 23 0.24 47.4 (37.9, 59.6) 44.8 (36.7, 59.1) 0.26 2 4 0.42 Medicare % Medicaid % Private insurance % 38 30 0.16 0.65 0.16 16 14 44 52 Lives alone % Daughters Left ventricular ejection fraction 24 1 (0, 2) 27 1 (1, 2) 0.64 0.31 0.45 0.93 26.5 (20, 35) 25 (20, 35) NYHA (New York Heart Association) 3 (3, 4) 3 (3, 4) Number of hospitalizations in prior 12 mo 2 (1, 4) 2 (1, 3) Coronary artery disease % Atrial fibrillation % Implantable cardiac defibrillator % Diabetes mellitus % Chronic obstructive pulmonary disease % Non compliance with diet % Current smoking % Heart rate supine (bpm) Mean arterial blood pressure (mm Hg) 66 32 65 43 0.22 0.88 0.13 0.56 20 23 43 26 34 0.11 0.49 23 18 12 15 81 (69, 96) 0.15 0.77 0.42 14 84 (71, 96) 90 (76, 100) 96 (83, 107) 0.02 Admission weight (pounds) 185 (155, 226) 194 (162, 220) 0.78 QRS interval (ms) Hemoglobin (g/dl) Serum sodium Blood urea nitrogen Serum creatinine 117 (92, 147) 12.3 (10.8, 13.7) 127 (98, 161) 0.16 12.4 (11.1, 13.7) 0.54 138 (135, 141) 140 (137, 141) 0.11 28 (19, 43) 25 (18, 37) 1.3 (1.0, 1.7) 0.14 1.4 (1.0, 1.9) 0.27 Data are expressed as median and interquartile range, or percentages, as appropriate. Downloaded for Anonymous User (n/a) at Florida State University from ClinicalKey.com by Elsevier on March 02, 2022. For personal use only. No other uses without permission. Copyright @2022. Elsevier Inc. All rights reserved. 236 N.V.A. Kommuri et al./Patient Education and Counseling 86 (2012) 233-238 Table 2 Paired comparisons of knowledge in study population. Knowledge Control Education p value Baseline n=137 3 month follow up (p') n=114 Baseline n=128 3 month follow up (p ) n=113 DSK score 5 (4, 6) 4 (2, 5) 5.5 (4, 6) (0.39) 4 (2, 5) (0.32) 9 (7, 12) (0.23) 6 (4, 7) 4 (3, 5) 6 (4, 7) (0.57) 0.32 5 (4,7) (<0.001) 0.55 DMK score Total score 9 (7, 11) 9 (7, 11) 11 (8.5, 13) (<0.001) 0.33 Data are expressed as median and interquartile range. Abbreviations: DSK - dietary sodium knowledge; DMK - disease management knowledge. * Comparison between baseline and 3 month follow up period. + Comparison between baseline for Control and Education groups. Table 3 Change in knowledge at 3 month follow-up in the study population. Control n=114 Education n=113 p value DSK score 0 (-1, 2) 0 (-1, 2) 0.87 DMK score 0(-1,1) 1 (0, 3) <0.001 Total score 0 (-2, 2) 1 (0, 4) 0.007 Data are expressed as median and interquartile range. Table 4 Association between Heart Failure Knowledge Questionnaire scores and clinical outcomes. No event Event p Baseline HFKQ n=119 n= 146 DSK score 6 (4, 7) 5 (4, 6) 0.352 DMK score 4 (2, 5) 3 (2, 5) 0.136 Total score 9 (7, 11) 9 (7, 11) 0.131 3 month follow up HFKQ DSK score n=110 n=117 6 (4, 7) 5 (4, 6) 0.068 DMK score 5 (3, 7) 11 (8, 13) 4 (3, 5.5) 10 (7, 12) n=117 0.001 Total score 0.002 Changes in HFKQ compared to baseline DSK score n=110 0 (-2, 2) 0(-1, 1) 0.416 DMK score 1 (0, 3) 1 (-1, 2) 0.045 Total score 1 (-2, 4) 1 (-1, 2) 0.072 Data are expressed as median and interquartile range. Patients randomized to education had significantly higher total HFKQ score increases at 3 months compared to patients receiving standard discharge information (1, 0 to 4 vs 0, -2 to 2, p = 0.007) as shown in Table 3. Specific performance on the subset of questions regarding DMK also improved with nurse education (1, 0 to 3 vs 0, -1 to 1, p < 0.001). No significant changes in DSK were seen with nurse education (0, -1 to 2 vs 0, -1 to 2, p = 0.87). Multivariate linear regression showed that patient group assignment to nurse education (beta 0.871, OR 2.39, 95% CI 1.33-4.31, p = 0.004) and duration of heart failure less than 3 months (beta 1.045, OR 2.84, 95% CI 1.41-5.73, p = 0.003) were found to be independent predictors of improved heart failure knowledge scores. Mediator analysis to understand the relationship between the achieved disease specific knowledge and the clinical outcome while controlling for the patient treatment assignment showed that the total HFKQ score at the 3 month time period was strongly associated with the clinical outcome at 180 days. The total HFKQ score at 3 months was inversely associated with clinical events, where beta = - 0.110, OR 0.896 (95% CI 0.827-0.970), p = 0.007. Of the 265 enrolled patients, 146 had clinical events during the 6 month follow-up. 136 patients were readmitted to the hospital, and 25 patients died during the 6 month follow up period. Twenty- three patients in the control group and 15 patients in the education group did not complete the 3 month follow-up HFKQ either due to death or refusal to complete the questionnaire. Patients experienc- ing clinical events were found to have similar baseline HFKQ scores when compared to patients without any clinical events (Table 4). Patients experiencing a clinical event were found to have a significantly lower total HFKQ scores (10, 7 to 12 vs 11, 8 to 13, p = 0.002) and DMK scores (4, 3 to 5.5 vs 5, 3 to 7, p = 0.001) at the 3 month follow-up examination. DSK scores at 3 months showed a nonsignificant trend to being higher for the event free patients (6, 4 to 7 vs 5, 4 to 6, p = 0.068). Furthermore, changes in the DMK score (from baseline to 3 month follow-up), but not the DSK score, were associated with clinical events (1, 0 to 3 vs 1, -1 to 2, p = 0.045). Changes in the total HFKQ score were higher in the patients without clinical events, but this difference did not reach statistical significance (p = 0.072). The associations between total HFKQ scores and changes in HFKQ scores at 3 month follow-up and self reported compliance with heart failure self care measures are shown in Table 5. Patients reporting adherence to recommendations for daily weight monitoring, following a specific dietary sodium restriction and fluid restriction, and reporting a plan for what to do if their Table 5 Association between Heart Failure Knowledge Questionnaire scores and self care measures. Compliant Not compliant p 3 month follow up HFKQ Daily weight monitoring Following sodium restriction Following fluid restriction 11 (8, 13), 133 9 (7, 11), 93 <0.001 13 (11, 14.5), 53 9 (7, 11), 173 <0.001 11 (8, 13.5), 97 9 (7, 12), 129 <0.001 Not smoking 10 (8, 12), 211 10 (7, 12), 15 0.394 Reports plan for worsened symptoms Performing exercise ≥3 times per week 10 (8, 13), 173 9 (7, 11), 53 0.009 10 (8, 13), 87 10 (7, 12), 139 0.082 Changes in HFKQ compared to baseline Daily weight monitoring 1 (-1, 4), 133 0 (-2, 2), 93 0.013 Following sodium restriction Following fluid restriction Not smoking 2 (1, 5), 53 0 (-2, 3), 173 0.015 2 (0, 4), 97 0 (-2, 2.5), 129 0.003 1 (-1, 3), 211 0 (-2, 2), 15 0.460 Reports plan for worsened symptoms 1 (-1, 3.5), 173 0 (-2, 2), 53 0.037 Performing exercise ≥3 times per week 1 (-1, 3), 87 1 (-2, 3), 139 0.34 Data are expressed as median (interquartile range), and n for group. Downloaded for Anonymous User (n/a) at Florida State University from ClinicalKey.com by Elsevier on March 02, 2022. For personal use only. No other uses without permission. Copyright @2022. Elsevier Inc. All rights reserved. 237 N.V.A. Kommuri et al./ Patient Education and Counseling 86 (2012) 233-238 symptoms worsened demonstrated significantly higher scores on HFKQ testing. Similarly, patients following these measures were more likely to have increases in their HFKQ scores at 3 months compared to baseline. At 3 month follow-up, HFKQ scores and changes compared to baseline did not differ in patients based on their adherence to smoking and exercise self care measures. 4. Discussion and conclusion 4.1. Discussion Findings from this study show that face to face nurse education significantly improves disease specific knowledge compared to the standard discharge process. Specifically, this patient targeted education program improved heart failure patient overall disease specific knowledge, and disease management knowledge, but did not significantly increase dietary sodium knowledge. This study also demonstrates that heart failure disease specific knowledge is associated with clinical outcomes in patients with heart failure, as patients without clinical events had higher increases in heart failure knowledge scores compared to patients experiencing clinical events in the 6 month follow up period. Patients randomized to receive the education intervention were found to be more than 2- fold more likely to have improved HFKQ scores at three months compared to controls receiving the standard discharge process. Multiple previous studies demonstrated that multidisciplinary discharge education with post discharge follow up improves clinical outcomes [3-12]. Our previous publication first described the independent effects of nurse education on clinical outcomes in patients with systolic heart failure, demonstrating a 35% reduction in rehospitalization in patients randomized to the nurse education intervention [7]. Prior studies have also demonstrated that there is a wide gap between the perceived learning needs of the patients when compared to health care professionals [19-21]. While changes in heart failure knowledge have been reported with disease specific interventions by others [22-24], no studies have assessed the association between knowledge acquisition and subsequent self-care behavior [24]. Furthermore, none of these previous studies have shown that a measurable improvement in the knowledge is associated with clinical outcomes. Findings from our study showed that heart failure knowledge is strongly associated with self reported adherence to heart failure self care measures. Patients reporting adherence with daily weight monitoring, dietary sodium and fluid restriction, and having a plan for what to do if their symptoms worsened had significantly higher HFKQ scores and higher improvement in HFKQ scores compared to patients reporting that they were not adherent to these recom- mendations. This observation supports the connections between the education intervention, the improvement in disease specific knowledge and the desired self care behaviors. It is plausible that these improved behaviors accounted for the better clinical outcomes demonstrated in the education group. Patients who retain educational principles conveyed by the nurse educator are more likely to practice appropriate self-care behaviors and alter their clinical course. Ni et al. previously demonstrated a trend toward an association between poor adherence to self care measures and lack of knowledge about self care. [25] This study did not assess the relationship between self care knowledge and clinical outcomes. Although we were able to demonstrate improvements in overall heart failure knowledge using the education intervention, we were not able to show improvements in dietary knowledge. This possibly points out a significant weakness in our educational program. The HFKQ was written for the purpose of assessing patient disease specific and dietary specific knowledge before and after the education intervention. The questionnaire has not been previously studied and attributes such as reliability and validity cannot be quoted. Previous studies demonstrated that specific education delivered by a registered dietician aimed at teaching skills for reading Nutritional Facts labels and sorting foods into high and low sodium groups led to clear improvements in patient's sodium knowledge [26]. Whether our education intervention would lead to improved ability to sort foods based on sodium content is unknown. Further refinements in our education program may need to include specific attention to Nutritional Facts label interpretation. Never- theless, while patients randomized to receive the education intervention did not improve their performance on the dietary sodium questions of the HFKQ, they reported clear improvement in adherence to dietary self care measures. Previous investigators have described the potential challenges surrounding the education of patients with chronic illness, including heart failure [22]. Medications, blood flow and prior central nervous system insults may directly determine the cognitive abilities of patients presenting with heart failure. These issues, combined with the heterogeneity of educational level, vocabulary, prior knowledge, and reading/oral literacy, strongly influence the success of educational efforts in the heart failure population. Others have shown that despite concerted efforts to provide medication information, patients may not necessarily retain the information on the first try [27]. This had led many to suggest that education for chronic illnesses should be performed over multiple interactions [28], rather than just one, as was the case in this study. 4.2. Conclusion This study demonstrates that a single face to face, 1 h long, educational session with a nurse educator leads to improved heart failure specific knowledge in patients hospitalized with heart failure and left ventricular systolic dysfunction. The knowledge that patients retained from the education session was apparent on testing at the 3 month follow up period, and this was strongly associated with appropriate self care behaviors. Furthermore, we have shown that patients with high heart failure knowledge scores are less likely to be readmitted to the hospital over a 6 month follow up period than patients with low scores. 4.3. Practice implications Nurse led education sessions are effective in improving disease specific knowledge as well as clinical outcomes in heart failure patients with systolic dysfunction. Our study highlights the need for funding of educational sessions to reduce the cost burden of this common chronic illness. Funding sources Quality Care Research Fund from the Academic Medicine and Managed Care Forum. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.pec.2011.05.019. References [1] Adams KF, Lindenfeld J, Arnold JMO, Baker DW, Barnard DH, Baughman KL, et al. Executive summary: HFSA 2006 Comprehensive Heart Failure Practice Guideline. J Card Fail 2006;12:10-38. [2] Hunt SA, Abraham WT, Chin MH, Feldman AM, Francis GS, Ganiats TG, et al. 2009 focused update incorporated into the ACC/AHA 2005 Guidelines for the Diagnosis and Management of Heart Failure in Adults. Circulation 2009;119: e391-479. Downloaded for Anonymous User (n/a) at Florida State University from ClinicalKey.com by Elsevier on March 02, 2022. For personal use only. No other uses without permission. Copyright @2022. Elsevier Inc. All rights reserved. 238 N.V.A. Kommuri et al./Patient Education and Counseling 86 (2012) 233-238 [3] Cline CM, Israelsson BY, Willenheimer RB, Broms K, Erhardt LR. Cost effective management programme for heart failure reduces hospitalisation. Heart 1998;80:442-6. [4] Gwadry-Sridhar FH, Flintoft V, Lee DS, Lee H, Guyatt GH. A systematic review and meta-analysis of studies comparing readmission rates and mortality rates in patients with heart failure. Arch Intern Med 2004;164:2315-20. [5] Hanumanthu S, Butler J, Chomsky D, Davis S, Wilson JR. Effect of a heart failure program on hospitalization frequency and exercise tolerance. Circulation 1997;96:2842-8. [6] Holland R, Battersby J, Harvey I, Lenaghan E, Smith J, Hay L. Systematic review of multidisciplinary interventions in heart failure. Heart 2005;91:899-906. [7] Koelling TM, Johnson ML, Cody RJ, Aaronson KD. Discharge education improves clinical outcomes in patients with chronic heart failure. Circulation 2005;111:179-85. [8] Krumholz HM, Amatruda J, Smith GL, Mattera JA, Roumanis SA, Radford MJ, et al. Randomized trial of an education and support intervention to prevent readmission of patients with heart failure. J Am Coll Cardiol 2002;39:83-9. [9] McAlister FA, Stewart S, Ferrua S, McMurray JJ. Multidisciplinary strategies for the management of heart failure patients at high risk for admission: a systematic review of randomized trials. J Am Coll Cardiol 2004;44:810-9. [10] McMurray JJ, Stewart S. Nurse led, multidisciplinary intervention in chronic heart failure. Heart 1998;80:430-1. [11] Phillips CO, Singa RM, Rubin HR, Jaarsma T. Complexity of program and clinical outcomes of heart failure disease management incorporating specialist nurse- led heart failure clinics. A meta-regression analysis. Eur J Heart Fail 2005;7:333-41. [12] Rich MW, Beckham V, Wittenberg C, Leven CL, Freedland KE, Carney RM. A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure. New Engl J Med 1995;333:1190-5. [13] Clark RA, Inglis SC, McAlister FA, Cleland JG, Stewart S. Telemonitoring or structured telephone support programmes for patients with chronic heart failure: systematic review and meta-analysis. Brit Med J 2007;334:942. [14] Harrison MB, Browne GB, Roberts J, Tugwell P, Gafni A, Graham ID. Quality of life of individuals with heart failure: a randomized trial of the effectiveness of two models of hospital-to-home transition. Med Care 2002;40:271-82. [15] Klersy C, De Silvestri A, Gabutti G, Regoli F, Auricchio A. A meta-analysis of remote monitoring of heart failure patients. J Am Coll Cardiol 2009;54:1683-94. [16] Kozak AT, Rucker-Whitaker C, Basu S, Mendes de Leon CF, Calvin JE, Grady KL, et al. Elements of nonpharmacologic interventions that prevent progression of heart failure: a meta-analysis. Congest Heart Fail 2007;13:280-7. [17] Matthews JC, Johnson ML, Koelling TM. The impact of patient-specific quality- of-care report cards on guideline adherence in heart failure. Am Heart J 2007;154:1174-83. [18] Mackinnon DP, Lockwood CM, Hoffman JM, West SG, Sheets V. A comparison of methods to test mediation and other intervening variable effects. Psychol Methods 2002;7:83-104. [19] Frattini E, Lindsay P, Kerr E, Park YJ. Learning needs of congestive heart failure patients. Prog Cardiovasc Nurs 1998;13:11-6. [20] Luniewski M, Reigle J, White B. Card sort: an assessment tool for the educa- tional needs of patients with heart failure. Am J Crit Care 1999;8:297-302. [21] Wehby D, Brenner PS. Perceived learning needs of patients with heart failure. Heart Lung 1999;28:31-40. [22] Baker DW, Asch SM, Keesey JW, Brown JA, Chan KS, Joyce G, et al. Differences in education, knowledge, self-management activities, and health outcomes for patients with heart failure cared for under the chronic disease model: the improving chronic illness care evaluation. J Card Fail 2005;11:405-13. [23] DeWalt DA, Malone RM, Bryant ME, Kosnar MC, Corr KE, Rothman RL, et al. A heart failure self-management program for patients of all literacy levels: a randomized, controlled trial. BMC Health Serv Res 2006;6:30. [24] Yehle KS, Sands LP, Rhynders PA, Newton GD. The effect of shared medical visits on knowledge and self-care in patients with heart failure: a pilot study. Heart Lung 2009;38:25-33. [25] Ni H, Nauman D, Burgess D, Wise K, Crispell K, Hershberger RE. Factors influencing knowledge of and adherence to self-care among patients with heart failure. Arch Intern Med 1999;159:1613-9. [26] Neily JB, Toto KH, Gardner EB, Rame JE, Yancy CW, Sheffield MA, et al. Potential contributing factors to noncompliance with dietary sodium restriction in patients with heart failure. Am Heart J 2002;143:29-33. [27] Cline CM, Bjorck-Linne AK, Israelsson BY, Willenheimer RB, Erhardt LR. Non- compliance and knowledge of prescribed medication in elderly patients with heart failure. Eur J Heart Fail 1999;1:145-9. [28] Fredericks S, Beanlands H, Spalding K, Da Silva M. Effects of the characteristics of teaching on the outcomes of heart failure patient education interventions: a systematic review. Eur J Cardiovasc Nurs 2010;9:30-7. Downloaded for Anonymous User (n/a) at Florida State University from ClinicalKey.com by Elsevier on March 02, 2022. For personal use only. No other uses without permission. Copyright @2022. Elsevier Inc. All rights reserved.See Answer
Q3:3. Define the following, Maximum Sustainable Yield and Carrying Capacity. 4. Let F(X) be the Growth Function and X be the fish stock then F'(X) = dF(X)/dX is the first-order derivative of the growth function. Translate the following mathematical expression into words: F'(x) = 0 F'(x) > 0 F'(x) < 0See Answer
Q4:2. Consider the graph. What is the y axis measuring? What is the x-axis measuring? For each point, (a), (b), and (c), answer the following: What is happening to growth at that value of x? Why? If left un-altered how would the fish population grow at this level of x? 3. Define the following. Maximum Sustainable Yield and Carrying Capacity.See Answer
Q5: ● CY6065 Water Maze Comprehension Datasheet For your answers, do not do a full report; simply answer the questions exactly as numbered below (a) to (d). CB Feb 2024 Work that is not clear or not presented in a professional, logical, concise way will lose marks. Marks will be deducted for: - pages of irrelevant statistical data; - untidy / poorly assembled work; - poor explanations; - inappropriate statistical comparisons. The usual rules regarding plagiarism apply - please don't! Check with me (CB) if you are not sure. Work must be submitted on-line as a single file via "on-line submission" in Weblearn. Questions 1. Does scopolamine produce a cognitive defect as demonstrated by significant changes in the performance of animals in the water maze? 2. If there is an effect, is this changed by the concurrent administration of the anticholinesterases neostigmine or physostigmine? a) From the Excel spreadsheet provided, calculate (i) the t-test p-values for each day for each treatment group compared with its appropriate control(s) using Excel's two sample t- test assuming equal variances. (ii) Calculate the means of your data sets + SEMS (standard errors of the mean), and present these, along with the p-values, in three tables (scopolamine vs control (“vehicle”); scopolamine vs scopolamine plus neostigmine; scopolamine vs scopolamine plus physostigmine). 20 marks b) Plot the means of your data onto a total of two line graphs. You may use hand-drawn graphs, or you can use appropriate software. Graphs should be of path length vs time (i.e. day number). One graph should show scopolamine data vs vehicle data (i.e two sets of data) over 4 days. The other graph should show the effects of concurrent administration of each anticholinesterase with scopolamine, compared to scopolamine alone (three sets of data). For each data point add SEM error bars and asterisks denoting statistical significance. Please do not submit photographs of graphs, use scanned images. d) Referencing 30 marks c) Give a professionally-written summary of your findings by addressing questions (1) and (2) above, and justify your answers using your statistical data (p-values) judiciously (max. 400 words total). Your answer should include a comment on the probable pharmacological mechanisms involved (include references where appropriate). 45 marks 5 marksSee Answer
Q6: STEVENS INSTITUTE OF TECHNOLOGY 1870 HOMEWORK 8 MA 541-B - Spring 2024 Show ALL WORK to get full credit. (Write the pledge on top of your work and sign under it.) Note: In your submission, you must do the following: Please manually solve all the questions and show the "Calculations" that you are doing, please don't just write the formula and the final value. Also, calculations should be very precise to get the full points. If you are just writing the formula and directly the final value, it will lead to points deduction. • Round all test statistics to four decimal places. Problem 1: Adult-onset diabetes is known to be highly genetically determined. A study was done comparing frequencies of a particular allele in a sample of such diabetics and a sample of nondiabetics. The data are shown in the following table: Bb or bb BB Diabetic 12 39 Normal 4 49 a) Are the relative frequencies of the alleles significantly different in the two groups? Use α = 0.01. b) What is the relevant odds ratio? Problem 2: Phillips and Smith(1990) conducted a study to investigate whether people could briefly postpone their deaths until after the occurrence of a significant occasion. The senior woman of the household plays a central ceremonial role in the Chinese Harvest Moon Festival. Phillips and Smith compared the mortality patterns of old Jewish women and old Chinese women who died of natural causes for the weeks immediately preceding and following the festival, using records from California for the years 1960-1984. Compare the mortality patterns shown in the table. (Week -1 is the week preceding the festival, week 1 is the week following, etc.) Use α = 0.05. Week Chinese Jewish -2 55 141 -1 33 145 1 70 139 2 49 161 Problem 3: Overfield and Klauber (1980) published the following data on the incidence of tuberculosis in relation to blood groups in a sample of Eskimos. Is there any association of the disease and blood group within the ABO system? Use α = 0.005. ABO system Severity Moderate-Advanced О A B AB 7 5 3 13 Minimal Not Present 27 32 8 18 55 50 7 24 Problem 4: Records of 317 patients at least 48 years old who were diagnosed as having endometrial carcinoma were obtained from two hospitals (Smith et al. 1975). Matched controls for each case were obtained from the two institutions; the con- trols had cervical cancer, ovarian cancer, or carcinoma of the vulva. Each control was matched by age at diagnosis (within four years) and year of diagnosis (within two years) to a corresponding case of endometrial carcinoma. This sort of design, called a retrospective case-control study, is frequently used in medical inves- tigations where a randomized experiment is not possible. The following table gives the numbers of cases and controls who had taken estrogen for at least 6 mo prior to the diagnosis of cancer. Is there a significant relationship between estrogen use and endometrial cancer? Do you see any possible weak points in a retrospective case-control design? Use a = 0.005. Controls Estrogen Used Not Used Cases Estrogen Used Not Used 39 113 15 150 Problem 5: Suppose that a company wishes to examine the relationship of gender to job sat- isfaction, grouping job satisfaction into four categories: very satisfied, somewhat satisfied, somewhat dissatisfied, and very dissatisfied. The company plans to ask the opinions of 100 employees. Should you, the company's statistician, carry out a chi- square test of independence or a test of homogeneity?See Answer
Q7: Instructions 1. Familiarise yourself with the above scenario, the data in the body condition scoring excel spreadsheet and how body condition scores are collected and used in sheep management. Lectures 5 and 13-15 and this video are good resources to begin with. There are also scientific papers in your reading list. 2. Summarise the data in the body condition scoring excel spreadsheet and produce a figure/s or table/s of the summary data. 3. Use the provided template to write a technical report on this body condition scoring activity and include a management plan for what you would do and the resources you would use from today until the end of winter (August 31st). Remember that many of these animals will be leaving the property at the end of May. 4. Check your work against the rubric that will be used for marking 27 021 98 AT3 Ani... 550 Writing the report Use the provided template for your report. Do not delete any sections (apart from the red instruction text) and ensure you fill in the provided management plan table. The word count is 1200 (± 10%). Note that you will not be penalised if the report succinctly addresses all the criteria, but penalties will apply for reports over the word limit or verbose and wordy. Below are some extra details on what should be included in each section: Executive summary. This is where you present a summary of what your report will be about and what the key findings are. Briefly state why this activity was undertaken, what was done, and what was found. This summary should be 1-2 paragraphs in length (no more than 300 words). Introduction Introduce all the key background material for your report and support with the scientific literature (i.e. references). This may include information about: . What a body condition score is . How body condition scores can be used in sheep management • Energy requirements during growth of young animals • Supplementary feeding Energy requirements during growth of young animals Supplementary feeding Methods Fully describe the data collection in enough detail that another person would be able to replicate the data collection. Include information about: • the location where the data was collected • the animals used • how the data was collected how you manipulated or summarised the data Results Present the summary figure/s or table/s that you have made using the data in the Sheep body condition score spreadsheet. Any figure presented must have a figure legend (below the figure) that describes the figure clearly enough so that a reader could understand what the figure is without reading the rest of the report. Any table presented must have a table header (above the table) that describes the figure clearly enough so that a reader could understand what the figure is without reading the rest of the report. Your figure or table must also be accompanied by text that describes what the major findings are. This may only be a couple of sentences for this report. Discussion Here you should put the results into context using the literature. You should consider the robustness of the method used and make any suggestions for future improvements or measurements to be taken. Menegerent plen Could understand what the figure is without reading the rest of the report. Your figure or table must also be accompanied by text that describes what the major findings are. This may only be a couple of sentences for this report. Discussion Here you should put the results into context using the literature. You should consider the robustness of the method used and make any suggestions for future improvements or measurements to be taken. Management plan Your management plan should describe how you would manage this mob of sheep through to the end of winter. Consider the body condition scores and weights at the starting point (now). Use the literature and scenario to decide on targets for the different groups of animals (e.g. replacement ewes, wethers for prime lamb etc) and key timepoints and describe the variety of management tools or practices available to you to achieve your target. Use some references to support your text and demonstrate that it aligns with industry best practice. Summary/conclusions The last short section (1-3 sentences) should summarise the key findings and, if relevant, draw some conclusions. References All material that is not your own original thought must be referenced using the APA 7 referencing style. This page from Concordia St Paul university in the USA may also be useful for using the APA7 referencing style.See Answer
Q8: Spring 2024 Assignment 2: SOC386L/SDS385 Briefly answer the following questions. Please include selected segments of computer code you used in your write-up if needed. You may consult with other students, but the work you hand in should reflect your own thinking. Background. The data set (RiesbyWide.dta) posted on Canvas comes from a study by Riesby et al. (1977) in which hospitalized depressed patients were treated for 5 weeks with imipramine. Clinical rating of depressive symptoms was carried out once weekly by Hamilton's Rating Scale (HRS). The data are in wide form as follows: id HamDO HamD5, EndoG, where id is the subject identifier and HamD0-HamD5 are depression measures (HamDO is the baseline or initial measurement) and Endog identifies subjects whose depression, as classified on the WHO Depression Scale, was "endogenous" or "non-endogenous" depression, with "endogenous" roughly pertaining to clinical depression in current practice. 10 points each. 1. Convert these data from the individual-level format to the "person-period" format (i.e., from wide to long). Carry out a basic exploratory analysis by graphing the raw trajectories for each subject (or randomly selected subjects) along with the linear fit through each individual's measurements in side-by-side plots (e.g., spaghetti plots). Comment on whether a linear growth curve model would seem appropriate given the observed and fitted patterns. 2. Fit an unconditional means model to these data and assess whether this model is an improve- ment over a simple regression model and why? 3. Fit an unconditional growth model to these data using a full model specification for the variance components (i.e., a model that estimates the variance of the random slope and intercept as well as their covariance). Use a likelihood ratio test to determine if this model offers an improvement over the unconditional means model. 4. Using a likelihood ratio test, test whether a more parsimonious unconditional growth model fits these data as well as the model used in Question 3. Use the preferred model as the "working" model. Interpret the fixed effects and variance components from your working unconditional growth model. 5. Under the assumptions of normality of the MLEs (i.e., asymptotic normality) we can determine some aspects of the distribution of random slopes in the depressed population. Using the slope fixed effect and the estimated variance of the random slope as a gauge of variability of the individual slopes around the fixed effect, about what proportion of the random slopes in the depressed population would you expect to be greater than 0? 6. Using the properties of MLEs we can determine some aspects of the distribution of random intercept (i.e., initial levels) in the depressed population. Using the intercept fixed effect and the estimated variance of the random intercept as gauge of variation in initial depression levels, about what proportion of the random intercepts in the depressed population would be expected be less than 20? 7. Obtain estimates of the random slope by predicting the random effect U₁; for each subject and adding these to the fixed effect ₁. Obtain estimates of the random intercept by predicting the random effect Uo; for each subject and adding these to the fixed effect Bo. Provide a histogram of the random slopes and intercepts. 1 8. Using your preferred model from Question 4, assess whether there is evidence that the "endoge- nous depression" classification is able to statistically differentiate between depression patients' initial levels of depression and also whether there is evidence that this classification moderates the change in depression scores over time. Extra Credit Problems. (2 points) Consider the OLS estimates of the individual-level slopes obtained from the marital adjustment data (see handouts 1-2). Use the information in the handout to obtain estimates of the slopes and their standard errors. We can follow the steps spelled out in the Bryk and Raudenbush article (available on Canvas) to improve upon these estimates as follows: • Denote the slope for the ith subject by bį. The total variance in the individual slope is a function of the sampling variance and the parameter variance. • The parameter variance is simply the squared standard error of the slope from the OLS model, denoted by se(bi)² = vi. • The parameter variance is the variance in the slopes, estimated as 7 = Σ¿(bi − b)²/(n − 1). • Define the weight function Wi=T/(t + vi) An improved estimate can be obtained as a weighted average of the OLS slope and the average slope. That is, b* = bįWį + (1 − W;)b 1. Use the individual slope estimates and their std. errors from handouts 1-2 to obtain the improved estimates and plot them against the original OLS estimates. Explain in what sense these estimates are "improved." ● 2. A simplified growth model can be fit using “centered” data, where the centered dependent variable is y¡ = Yij − Yi and tåj = tij – tį. Consider the following model Yij = Bitij + ε Bi = ß + Ui Discuss the differences between this model and the standard linear growth model. Fit this model as a linear mixed model. and 3. Compare the slope estimate (fixed effect) to the one from the centered model. Explain why they are similar or different. 4. Obtain the empirical Bayes estimates of the level-2 residuals, the Û¿. Compute the EB esti- mates of the slope as +₂. Compare these to the ones computed in the first extra-credit problem. 2See Answer
Q9:A Relaxin receptor agonist drug (RRA01) for the acute heart failure treatment is developed by the Sunny Pharmaceutical Company. It is a publicly traded company. The reduction of cardiovascular death (mortality) was used as the end point (results of the research) for this investigation. The null hypothesis is "there is no difference in the cardiovascular mortality reduction between patients who received RRA01 (treatment group) and those who did not receive RRA01 (control group). Discuss the impact (on the company and/or on the patients) of the following two possible clinical trial results to the Sunny Pharmaceutical Company, staff of the company, and the patients. Use a = 0.05 as the significance level for your discussion. 1. p = 0.002 as the hypothesis test results 2. p = 0.3 as the hypothesis test results.See Answer
Q10:[Hints for Discussion Board 2] You need to remember that the hypothesis test results show you the CHANE OF THE NULL HYPOTHESIS TO BE TRUE. The null hypothesis is "THERE IS NO DIFFERENCE between patients received treatment and patients did not receive the treatment". Usually we use significance level (a) of 0.05 or 0.01 for comparison. I will use a-0.05 for explanation. 1. p value of your hypothesis test results is SMALLER than 0.05 (a). --> the chance of the null hypothesis to be true is very small -> so you REJECT the null hypothesis. it means what you said in the null hypothesis (no difference in treatment results in subjects receives the treatment or not received the treatment) is NOT TRUE-> therefore the conclusion is "there is significant difference in the results between those who received the treatment and those who did not receive the treatment. Is this a GOOD TREATMENT? Imaging the treatment is for COVID-19 patients, should we be happy about it? Should the drug companies be happy about it? 2. p value of your hypothesis test results is GREATER than 0.05 (a). --> the chance of the null hypothesis to be true is BIG/possible so you FAIL TO REJECT the null hypothesis. -→> it means what you said in the null hypothesis (no difference in treatment results in subjects receives the treatment or not received the treatment) is TRUE -> therefore the conclusion is "there is no significant difference in the results between those who received the treatment and those who did not receive the treatment. Is this a GOOD TREATMENT? Imaging the treatment is for COVID-19 patients, should we be happy about it? Should the drug companies be happy about it?See Answer
Q11:4. We've talked a lot about the difference between correlation and causality. You read a study's conclusion that states that "having more social support causes increased levels of happiness." (10 points overall) a. What are some potential issues with the way the researchers established causality? (4 points) b. What steps are needed to establish causal order of social support and happiness? (3 points) c. Suggest one or two other variables that we might need to take into account when we're looking at the relationship between social support and happiness. (3 points)See Answer
Q12:Extra Credit (Optional): Please complete this table if you would like to gain some extra credit. (6 points total; 0.5 points per cell) Statistical test Chi-square t-test ANOVA Multiple Regression Types of variables appropriate in terms of level of measurement (LOM)? Or, any special rules for IV or DV? Goal or purpose of test (association, causality, etc.) Question the test seeks to answer?See Answer
Q13:actice 3 Question 13, 4.2.15 Part 1 of 2 Blood Types K Use the data in the following table, which summarizes blood groups and Rh types for randomly selected subjects. Assume that subjects are randomly selected from those included in the table. Rh Rh 0 78 20 Blood Groups A 67 16 are not HW Score: 77.19%, 14.67 of 19 points Points: 0 of 2 B 30 3 If two people are selected, find the probability that they are both type Rh in parts (a) and (b) below. www. are AB 27 2 a. Assume that the selections are made with replacement. Are the events independent? The probability is. The events type Rh affect the pro (Round to three decimal places as Save independent because the occurrence of the first subject having blood rrence of the second subject having blood type Rh".See Answer
Q14:(?) 1 7 0.5 points Set up the null hypothesis Ho and the alternative hypothesis H₂ for the following statement. The owner of a football team claims that the average attendance at games is over 67,800, and H is therefore justified in moving the team to a city with a larger stadium. Ho: U, the average attendance at games, is equal to 67,800 Ha: μ, the average attendance at games, is less than 67,800 Ho: μ, the average attendance at games, is greater than 67,800 H₂: U, the average attendance at games, is less than or equal to 67,800 Ho: μ, the average attendance at games, is less than 67,800 Ha: μ, the average attendance at games, is greater than or equal to 67,800 Ho: μ, the average attendance at games, is equal to 67,800 H₂: μ, the average attendance at games, is greater than 67,800 SubmitSee Answer
Q15:6 0.5 points . -0.01, Z-2.79, H₁ H₂>₂ IV c). A is the positive critical value for this question, what is/are the possible critical region(s) for this hypothesis test? Gretaer than A Smaller than A Greater than A or smaller than -A Greater than -A or smaller than A None of the aboveSee Answer
Q16:Part II a. Mann Whitney U test (4 points) For this part of the assignment, you will compare the quality of life (QOL_post) between patients (older than 70 years only) in the drug treatment group and patients in the drug + behavior treatment group after a 6-week treatment. The data to be used for this part of the assignment are saved as 'HW Mann Whitney.sav'. 1. A nonparametric Mann Whitney U test will be used to compare the two independent means. Write down the null and alternative hypotheses (1 point). 2. Provide descriptive statistics for QOL after treatment (QOL_post) (1 point). 3. Report the p value and state the hypothesis resolution (1 point). 4. Document your results (1 point). Part II b. Kruskal-Wallis test (6 points). For this part of the assignment, you will compare the post-treatment quality of life (QOL_post) for the patients (older than 70 years) with LUTS across all three treatment groups: drug treatment, behavior treatment, and drug + behavior treatment. The data to be used for this part are located in a file called 'HW Kruskal Wallis.sav. 1. A nonparametric Kruskal-Wallis test will be used to compare three independent means. Write down the null and alternative hypotheses (1 point). 2. Provide descriptive statistics for QOL after treatment (QOL_post) (1 point). 3. Report the p value and state the hypothesis resolution (1 point). 4. Report the post hoc analysis (2 points). 5. Document your results (1 point)./nPart II c. Wilcoxon Signed Ranks Test (4 points). For this final section of the assignment, you must evaluate whether the quality of life increased after the treatment, for the patients (older than 70 years) in the drug + behavior treatment group only. The data to be used for this analysis are saved as 'HW Wilcoxon Signed rank.sav'. 1. A nonparametric Wilcoxon Signed Ranks Test will be used to compare the paired means. Write down the null and alternative hypotheses (1 point). 2. Provide descriptive statistics for QOL before (QOL_pre) and after treatment (QOL_post) (1 point). 3. Report the p value and state the hypothesis resolution (1 point). 4. Document your results (1 point).See Answer
Q17:0.54 0.75 0.11 0.88 1.28 0.52 0.83 A food safety guideline is that the mercury in fish should be below 1 part per million (ppm). Listed below are the amounts of mercury (ppm) found in tuna sushi sampled at different stores in a major city. Construct a 95% confidence interval estimate of the mean amount of mercury in the population. Does it appear that there is too much mercury in tuna sushi? ... This question: 3 point(s) possible What is the confidence interval estimate of the population mean u? ppm <με ppm (Round to three decimal places as needed.) Does it appear that there is too much mercury in tuna sushi? Submit quiz OA. Yes, because it is possible that the mean is not greater than 1 ppm. Also, at least one of the sample values exceeds 1 ppm, so at least some of the fish have too much mercury. OB. Yes, because it is possible that the mean is greater than 1 ppm. Also, at least one of the sample values exceeds 1 ppm, so at least some of the fish have too much mercury. OC. No, because it is possible that the mean is not greater than 1 ppm. Also, at least one of the sample values is less than 1 ppm, so at least some of the fish are safe. 4 OD. No, because it is not possible that the mean is greater than 1 ppm. Also, at least one of the sample values is less than 1 ppm, so at least some of the fish are safe. Submit quiSee Answer
Q18:Here are summary statistics for randomly selected weights of newborn girls: n = 178, x= 30.8 hg, s=7.2 hg. Construct a confidence interval estimate of the mean. Use a 98% confidence level. Are these results very different from the confidence interval 29.4 hg <µ<33.0 hg with only 17 sample values, x= 31.2 hg, and s=2.9 hg? What is the confidence interval for the population mean μ? hg<μ<hg (Round to one decimal place as needed.) Are the results between the two confidence intervals very different? OA. Yes, because the confidence interval limits are not similar. O B. No, because each confidence interval contains the mean of the other confidence interval. OC. No, because the confidence interval limits are similar. O D. Yes, because one confidence interval does not contain the mean of the other confidence interval. 13 NextSee Answer
Q19:Question 4 of 7 Assume that we want to construct a confidence interval. Do one of the following, as appropriate: (a) find the critical value t/2. (b) find the critical value Za/2, or (c) state that neither the normal distribution nor the t distribution applies. OB. This quiz: 18 point(s) possible This question: 1 point(s) possible Here are summary statistics for randomly selected weights of newborn girls: n=227, x= 33.7 hg, s= 6.4 hg. The confidence level is 99%. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OA. ta/25 (Round to two decimal places as needed.) Submit quiz Za/2 (Round to two decimal places as needed.) OC. Neither the normal distribution nor the t distribution applies. 4See Answer
Q20:Assume that we want to construct a confidence interval. Do one of the following, as appropriate. (a) Find the critical value Za/2. (b) find the critical value ta/2, or (c) state that neither the normal nor the t distribution applies. Confidence level is 95%, o = 26.6, and the histogram of right-eye vision measurements from a random sample of 66 adult males is shown to the right. Frequency 40 30- 20 10 of 0 50 100 150 200 Vision in Right Eye Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OA. Za/2 (Round to two decimal places as needed.) OB. ta/2 (Round to two decimal places as needed.) OC. Neither the normal nor the t distribution applies. Next QSee Answer

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