Statistical Methods for Health Care Research

1. Statistical Methods for Health Care Research Chapter 1 Using Research and Statistics in Health Care

2. Types of Statistics • Descriptive • Numerical or graphic summaries of data • Charts, graphs, tables, summary statistics (e.g., mean and standard deviation) • Inferential • Statistical techniques that allow conclusions to be drawn about the relationships found among different variables • Examples include Chi-square test, t test, ANOVA.

3. Types of Studies • Descriptive and Explorative • Simply describe situations and events • Ask descriptive questions • “What is the average length of stay in a hospital after being admitted for an asthma attack?” • Descriptive statistics are used to analyze data from these studies.

4. Types of Studies (cont.) • Explanatory Studies • Elucidate relationships among variables • Ask inferential questions • Are women who are sedentary during the 3rdtrimester of pregnancy more likely to have a C-section than women who exercise regularly during the 3rd trimester? • Use inferential statistics • May or may not seek to establish causality

5. Types of Studies (cont.) • Prediction and Control • Seek to determine which variables predict other variables and to determine causality • Ask inferential questions • Are people who receive an experimental medication less likely to have symptoms of the disease than people who receive the standard medication? • Use inferential statistics

6. Question • True or False • Explanatory studies simply seek to describe situations and events.

7. Answer • False • Rationale: Explanatory studies seek to elucidate the relationships among variables.

8. Ten-Step Study Plan • 1. Statement of the problem and its significance • 2. Theoretical/conceptual framework • 3. Research questions to be answered • 4. List of hypotheses to be tested • 5. Definitions of key terms and variables

9. Ten-Step Study Plan (cont.) • 6. Description of the research design • 7. Description of the sample and how it was obtained • 8. Description of the planned statistical analysis • 9. Statement of assumptions and limitations • 10. Dissemination plan

10. Statement of Problem • Explain the Purpose of the Study • The research question • Why it is important? • How it fits into the existing body of research? • Be Clear and Concise • Clearly state what the study seeks to accomplish • Use phrases like “the purpose of this study is to…”

11. Theoretical/Conceptual Framework • All studies need an underlying framework that organizes the analysis. • Draw from existing theory or provide a logic model • Use the framework to organize your research questions and hypotheses • Use existing theoretical models where possible and cite appropriately

12. Research Questions • Research questions should stem directly from the statement of the purpose of the study. • Ground questions in theory and current literature • Be clear about the expected relationships • Relate directly to the data that will be gathered by the researcher

13. List of Hypotheses to be Tested • A hypothesis is a tentative prediction or description of the expected relationship between two or more variables. • Hypotheses translate research questions into statements that can be tested with inferential statistics. • There are two types of hypotheses: directional and nondirectional.

14. List of Hypotheses to be Tested (cont) • Directional (one-way) hypotheses state the expected direction of the relationship between the two variables: • People who are immunized will be less likely to contract the flu than people who are not immunized. • Nondirectional (two-way) hypotheses simply state that there will be a relationship between the variables: • There will be a relationship between obesity and exercise level.

15. Definitions of Key Terms and Variables • Define all terms that may be unclear to the reader • Write out all acronyms the first time they are used • Define all variables • Indicate whether the variables are dependent, independent, or covariates

16. Definitions of Key Terms and Variables (cont.) • Independent variables are those that are manipulated and/or may affect the outcome of interest. • These typically include age, gender, and ethnicity. • Dependent variables are the outcomes of interest. • These typically include health status, use of health services, and cost of care.

17. Question • True or False • Descriptive studies do not need a framework.

18. Answer • False • Rationale: All studies need to be organized using a theoretical or conceptual framework.

19. Description of the Research Design • Describe how the data will be or were collected. • Describe the type of study (observational, longitudinal, quasi-experimental, experimental) • Describe the way in which the data will be gathered (interview, survey, medical records, etc.) • If secondary data analysis, describe the study that provided the data and provide a citation for the study

20. Describe the Sample • Describe the sample • Type of sampling (random, nonrandom) • Sample size (overall and of each comparison group) • Sociodemographics (age/gender/ethnicity/education/marital status, other relevant variables)

21. Describe the Statistical Analysis • Explain how you plan on analyzing the data • How will you clean the data (e.g., make sure it is error free)? • What descriptive statistics will you use? • What inferential statistics will you use? • What type of models will you build (e.g., linear regression, logistic regression, ANOVA, others)?

22. Assumptions, Limitations, and Delimitations • Assumptions • Statements that are taken to be true even though you have no direct evidence about whether or not they are true • For example, in a study of exercise behavior, we assume that study participants are honest with us when they tell us how frequently they exercise.

23. Assumptions, Limitations, and Delimitations (cont.) • Limitations • Weaknesses of the study that may limit the validity of the results • Common limitations include small sample sizes, poor response rates, poor follow-up response rates, and lack of random selection.

24. Assumptions, Limitations, and Delimitations (cont.) • Delimitations • Boundaries to which the study was deliberately confined • For example, the study may focus on adults only, on a certain age group only, or on women only. • The delimitations limit the generalizability of the study.

25. Dissemination Plan • Dissemination is the way in which the results of the study are shared with others. • Internal reports • Presentations at conferences • Publications in trade journals • Publications in peer-reviewed journals

26. Question • Which of the following is an example of an assumption of a study? • The self-reported body weight was accurate. • Only women ages 18 to 34 were included in the study. • The response rate to the survey was only 33%. • All of these are assumptions.

27. Answer • A. The self-reported body weight was accurate. • Rationale: We would assume that our subjects correctly reported their body weight. Option B is a delimitation and option C is a limitation.

28. End of Presentation