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Survey Methodology Data interpretation and presentation

Survey Methodology Data interpretation and presentation. EPID 626 Lecture 11. References. Many elements of this lecture were taken from Fink, Arlene. How to Report on Surveys. Sage Publications. 1995. Babbie, Earl. Survey Research Methods. Wadsworth Publishing Company. 1990. Analytic modes.

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Survey Methodology Data interpretation and presentation

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  1. Survey MethodologyData interpretation and presentation EPID 626 Lecture 11

  2. References • Many elements of this lecture were taken from • Fink, Arlene. How to Report on Surveys. Sage Publications. 1995. • Babbie, Earl. Survey Research Methods. Wadsworth Publishing Company. 1990.

  3. Analytic modes • Univariate analysis • Examination of the distribution of cases on only one variable at a time • Aim is description • Example: SBP distribution among subjects • Bivariate analysis • Examination of the distribution of cases on one dependent and one independent variable • Aim is explanation • Example: SBP distribution by sex

  4. Analytic modes (2) • Multivariate analysis • Examination of the distribution of cases on one dependent and more than one independent variable • Aim is explanation • Example: distribution of SBP by race and sex

  5. Presenting univariate data Options (example=age): • List all respondents with their age • Tabulate the number of respondents within categories of age • Use measurements of central tendency and dispersion • Appropriate for continuous data

  6. Measures of central tendency • Mean • Average • Mode • The most frequent attribute • Median • The middle attribute in a ranked distribution of observed attributes

  7. Measures of dispersion • Range • Distance between the lowest and highest values • Often presented as min and max • Example • range= 40 • or range= 20-60 • Standard deviation • Distribution of observations about the mean

  8. Measures of dispersion (2) • Quartile deviation or semi-interquartile range • One-half of the distance between the bottom of the first quartile and the top of the fourth quartile

  9. Constructing bivariate tables • Column headings are determined by the most important comparison • cases vs. controls, men vs. women etc. • There are many options for format; decision should be made based on ease of interpretation

  10. Guidelines for formatting tables • Headings or titles should sufficiently describe what is in the table • The original content of the variable (the survey question) should be presented in the table or in accompanying text • Values or categories of each variable should be indicated

  11. Guidelines for formatting tables (2) • When presenting percentages, the base upon which they are computed should be indicated • Number of respondents with missing data should be indicated • If appropriate, statistical values (frequencies or percents) should be in descending order

  12. Example

  13. Guidelines for formatting tables (3) • Use a standardized set of symbols to call the reader’s attention to key aspects of the table • definitions • statistical significance • different denominator for % • P-value format • use “=“ for exact p-value • use “<“ for other p-values

  14. Presenting data “First you tell’em what you’re gonna tell’em, then you tell’em, then you tell’em what you told’em, and then you tell’em what to do with it.” -Preacher’s proverb

  15. Presenting data • A reader should be able to replicate your study • Data without methods is meaningless • A reader should be able to verify all percents and measures of association such as OR or RR

  16. Interpretation of results • Interpretation should follow the flow from your research question and study objectives • Interpretation should be guided by statistical significance as appropriate

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