Three partial questions, two full questions. (1-3 are partially complete...looking to have findings summarized)
NURS 701 - Statistical Analysis Questions – Assignment 3 (Due by Midnight – Sunday, September 27h, 2020) For each of the questions below, carry out an appropriate analysis to answer the research questions. The JMP files for some of the questions are located on the Datasets page on the course website. Most of the problems required you to enter the data yourself. When possible, include the relevant JMP output. 1. Improving control of blood glucose levels is an important motivation for the use of insulin pumps by diabetic patients. However, certain side effects have been reported with pump therapy. The table below comes from the paper “Acute complications associated with insulin pump therapy: Report of experience with 161 patients” by Mecklenberg et al. published in JAMA 252 (23), 3265-3269. The table provides data on the occurrence of diabetic ketoacidosis (DKA) in patients before and after pump therapy. Before pump therapy After pump therapy No DKA DKA Row Totals No DKA 128 7 135 DKA 19 7 26 Column Totals 147 14 n = 161 Conduct an appropriate test to determine if the rate of diabetic ketoacidosis (DKA) is higher following diabetic pump therapy. Summarize your findings. (5 pts.) 2. Schoenbaum et al. looked at risk factors for human immunodeficiency virus (HIV) infection among intravenous drug users enrolled in a methadone program in their paper “Risk factors for human immunodeficiency virus infection in intravenous drug users” published in the New England Journal of Medicine, 321 (13), 874-879. The data table below presented the HIV antibody status among 120 non-Hispanic white subjects by total family income. Family Income Level (ordinal) HIV Status A - < $10k="" b="" –="" $10k="" –="" $20k="" c="" -=""> $20k Row Totals HIV Positive 13 5 2 20 HIV Negative 59 21 20 100 Column Totals 72 26 22 120 Conduct a test to determine if total family income is related in a consistent manner to percentage of HIV-positive? Summarize your findings. (5 pts.) 3. In a study to investigate the potential relationship between age at first birth and the development of breast cancer the following results were obtained. Age at First Birth (ordinal) Case-Control status 1 < 20="" 2="" 20="" –="" 24="" 3="" 25="" –="" 29="" 4="" 30="" –="" 34="" 5=""> 35 Row Totals Case 320 1206 1011 463 220 3220 Control 1422 4432 2893 1092 406 10245 Column Total 1742 5638 3904 1555 626 n = 13,465 Is there evidence of an increasing trend in the proportion of breast cancer cases as a age at first birth increases? Conduct appropriate statistical test to answer this question and summarize the results. (5 pt.) 4. A case-control study was carried out to look at the potential risk for myocardial infarctions associated with oral contraceptive use. In addition to case-control status and current OC use, the age of the subject was also recorded. The variable age group described below is a ordinal variable created from the ages of the subjects. The data-file OC-Age-MI.JMP contains these data and the variables in this file and their coding are defined below. Case-Control Status 1 = Case (Myocardial Infarction (MI)) 2 = Control Oral Contraceptive Use? 1 = Yes 2 = No Age Group 1 = 25 - 29 yrs., 2 = 30 – 34 yrs., 3 = 35 – 39 yrs., 4 = 40 – 44 yrs., 5 = 45 – 49 yrs. a) Ignoring age group, estimate the risk for MI associated with OC use. Provide both a point estimate and an associated confidence interval for this measure of risk. Discuss. In doing this in JMP it will be best to use the OC coded and Case-Control coded so the risk measure is calculated in the preferred way. The appropriate 2x2 contingency table is shown below so you can easily check your calculation by hand. (5 pts.) b) What type of confounder would you expect age to be, positive or negative? Explain your reasoning by considering the relationship between age, oral contraceptive use, and myocardial infarctions. (3 pts.) c) The tables on the following page were obtained by stratifying on age group. Below each calculate the associated OR. Does age appear to be a confounder? What type given these results? Explain. (5 pts.) Age Group: 1 = 25 - 29 yrs., 2 = 30 – 34 yrs., 3 = 35 – 39 yrs., 4 = 40 – 44 yrs., 5 = 45 – 49 yrs. Age Group = 1 Age Group = 2 Age Group = 3 Age Group = 4Age Group = 5 d) Conduct an appropriate test to determine if a significant relationship exists between OC use and MI adjusting for the age group classification of the individual. Summarize your findings. (4 pts.) e) We can obtain a better estimate of the odds ratio than the crude one from the combined table in part (a) by combining the results from the age group stratified tables. The formula for this combined OR is given by where k = number of strata, (note: k = 5 in this case) and are the usual cells from strata i. Remember cell where risk factor and disease are present. This estimate of the odds ratio is known as Cochran-Mantel-Haenszel OR or . Find the for this study and compare it to the crude OR from part (a). What does the CMH odds ratio suggest about the risk OC use presents when considering myocardial infections? (5 pts.) 5. Rosenberg et al. (1980) studied the relationship between coffee drinking and myocardial infarction in young women, aged 30-49 years. This retrospective study including 487 cases hospitalized for the occurrence of a myocardial infarction (MI). Nine hundred eighty controls hospitalized for an acute condition (trauma, acute cholecystitis, acute respiratory diseases and appendicitis) were selected. The measured variables in this study are defined below. These data are contained in the file Coffee-MI.JMP. Case-Control Status 1 = Case (Myocardial Infarction (MI)) 2 = Control Drink Coffee? 1 = Yes (5 cups of coffee or more) 2 = No (< 5 cups of coffee) smoker group 1 = never., 2 = former, 3 = 1 – 14 cigarettes, 4 = 15 – 24 cigarettes, 5 = 25 – 34 cigarettes, 6 = 35 – 44 cigarettes, 7 = 45+ cigarettes a) ignoring smoking group, estimate the risk for mi associated with drinking coffee as defined above. provide both a point estimate and an associated confidence interval for this measure of risk. discuss. in doing this in jmp it will be best to use drink coffee? and case-control as coded above so the risk measure is calculated in the preferred way. the appropriate 2x2 contingency table is shown below so you can easily check your calculation by hand. (5 pts.) b) what type of confounder would you smoking status to be, positive or negative? explain your reasoning by considering the relationship between smoking status, coffee use as defined, and myocardial infarctions. (3 pts.) c) the tables below were obtained by stratifying on smoking status. below each calculate the associated or. does smoking status appear to be a confounder? what type given these results? explain. (7 pts.) never former 1 – 14 cigarettes 15 – 24 cigarettes 25 – 34 cigarettes 35 – 44 cigarettes 45+ cigarettes d) conduct an appropriate test to determine if a significant relationship exists between coffee use as defined and mi adjusting for the smoking status classification of the individual. summarize your findings. 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