1 / 33

Appendix A: Additional Topics

Appendix A: Additional Topics. Objectives. Identify specific cases for which the Categorical platform was designed. Summarize complex categorical data with the Categorical platform. Introduction. The purpose of the Categorical platform is to tabulate and summarize categorical response data.

tamyra
Télécharger la présentation

Appendix A: Additional Topics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Appendix A: Additional Topics

  2. Objectives • Identify specific cases for which the Categorical platform was designed. • Summarize complex categorical data with the Categorical platform.

  3. Introduction • The purpose of the Categorical platform is to tabulate and summarize categorical response data. • Test statistics are available, too. • The main advantage of the Categorical platform is that it recognizes common formats for complex data collection. • Surveys • Clinical trials • Quality assurance • This platform reduces or eliminates the need to reshape the data before analysis.

  4. Analysis Roles • Nine specific roles for the response (Y) are included. • These roles address the complex data formats (next). • The optional X role provides for grouping variables. • The levels define samples or sample groups. • The optional Sample Size role is used for calculation of the rate of occurrence. • The optional ID role is used to collect multiple responses that appear on separate rows.

  5. Response Role 1: Separate Responses • The responses occur individually, in separate columns. • Each response might have different categories. • A separate analysis is performed for each response.

  6. Response Role 2: Aligned Responses • All of the responses use the same categories.

  7. Response Role 3: Repeated Measures • All of the responses use the same categories, but they are measured more than once. • This role provides an optional transition report to determine whether categories change over time.

  8. Response Role 4: Rater Agreement • All of the responses use the same categories to rate the same item.

  9. Response Role 5: Multiple Response • All of the responses use the same categories that are entered into separate columns, but treated as a single grouped response.

  10. Response Role 6: Multiple Response by ID • All of the responses use the same categories that are entered into one column and one or more rows, but treated as a single grouped response. • Must use ID role to collect responses.

  11. Response Role 7: Multiple Delimited • All of the responses use the same categories that are entered into one column and one row, separated by commas.

  12. Response Role 8: Indicator Group • The responses are binary across multiple columns in a related group (ID).

  13. Response Role 9: Response Frequencies • The responses are counts across multiple columns in a related group (ID).

  14. Unique Occurrences • This option enables you to count a response level just once when it is duplicated for the same ID.

  15. Grouping Options • There are three options that control the results for your grouping variables (X): • Combinations: This option results in frequency reports for combinations of the samples. • Each Individually: This option results in frequency reports separately for each samples. • Both: This option results in frequency reports both ways described above.

  16. Report: Frequency • The Frequency report presents a tabulation of the counts for each category and the total counts (Responses) and total units (Cases). • Grouping variables (X) produce a stratified tabulation.

  17. Report: Share of Responses • The Share of Responses report presents a tabulation of the proportion of the total counts (Responses) for each category. • Grouping variables (X) produce a stratified tabulation.

  18. Report: Rate per Case • The Rate Per Case report presents a tabulation of the proportion of the total units (Cases) for each category. • Grouping variables (X) produce a stratified tabulation.

  19. Report Format • The reports are formatted as simple or stratified tables, one each for the frequency, share, and rate. • The Crosstab format optionally collects all three values into one cell. • The Table and Crosstab formats can be transposed.

  20. Chart: Share • The Share Chart presents a mosaic plot of the proportion of the total counts (Responses) for each category. • Grouping variables (X) produce a stratified tabulation.

  21. Chart: Frequency • This chart presents a bar chart of the frequency table. • Grouping variables (X) produce a stratified tabulation. • This chart is optional. It is not presented by default.

  22. Available Statistics • Test Response Homogeneity • Test Each Response • Relative Risk • Conditional Association • Agreement Statistic • Transition Report

  23. Test Response Homogeneity • Determine whether the proportions or probabilities are the same across all samples. • This marginal homogeneity test of independence is based on the Pearson chi-square test and the likelihood ratio chi-square test. • Typically used when there is one response variable and one explanatory variable. • Multiple explanatory variables are treated as one variable.

  24. Test Each Response • Determine whether the rates for each category are the same across all samples. • This test is based on Poisson regression. • Model each response category separately. • The test is a likelihood ratio test.

  25. Relative Risk (Optional) • The risk (probability) of each category is computed for each sample. • The risks are compared across samples. • This statistic requires the Unique occurrences within ID option in the launch dialog.

  26. Conditional Association (Optional) • The probability of each category is computed, given one of the other categories. • This statistic requires the Unique occurrences within ID option in the launch dialog.

  27. Agreement Statistic • Determine whether the ratings from each rater agree. • This requires Rater Agreement response role. • The responses must use the same categories. • This is stricter than association. • The agreement test is based on Cohen’s kappa statistic. • Determine whether the lack of agreement is symmetrical. • The symmetry test is based on Bowker and McNemar statistic.

  28. Transition Report • Determine whether the frequencies of categories have changed over time. • This requires the Repeated Measures response role. • This test is based on the counts and the rates of the transitions.

  29. Financial Advisor Survey Example • A small firm that provides financial management services sends a survey to customers to assess satisfaction. • Service Quality: rated Low, Medium, or High • Responsiveness: rated Low, Medium, or High • Years as Client • Type of Account: Individual or Business • Analyze Service Quality and Responsiveness over the samples of Years as Client and Type of Account.

  30. Transform Samples • Convert the continuous explanatory variable Years as Client to a categorical variable, Client Retention. • All survey respondents are current clients. • Client Retention: New (1 to 3), Steady (4 to 8), or Loyal (>8)

  31. Categorical Platform This demonstration illustrates the concepts discussed previously.

  32. Exercise This exercise reinforces the concepts discussed previously.

More Related