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Which statistical method?

This guide explores how to determine the appropriate statistical test for your research questions. It outlines the process of identifying response and predictor variables, highlighting key types such as quantitative and qualitative. The document provides a structured approach to formulating questions, with examples including correlation, logistic regression, t-tests, ANOVA, and survival analysis. It emphasizes understanding how to answer questions about relationships and differences between groups, as well as scenarios where no differences are concluded.

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Which statistical method?

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  1. Which statistical method? How to decide if the correct statistical test was used Al Best, PhD David Sarrett, DMD, MS

  2. What’s the question? • Questions are of the form: • For ___ response variable, is there a relationship with ___ predictor variable? • For ___ response variable, is there a difference between the groups identified by the ___ predictor variable? • Look at the predictor variable first.

  3. Predictor variable: • Quantitative (numeric)continuous or discrete • Qualitativenominal or ordinal • Special casetime to an event

  4. Predictor variable: • Quantitative (numeric)continuous or discrete • Qualitativenominal or ordinal • Special casetime to an event

  5. Predictor variable: • Quantitative (numeric)continuous or discrete • Qualitativenominal or ordinal • Special case:time to an event

  6. What’s the question? • Questions are of the form: • For ___ response variable, is there a relationship with ___ predictor variable? • For ___ response variable, is there a difference between the groups identified by the ___ predictor variable? • Now look at the outcome variable next.

  7. Response variable: • Quantitative (numeric)continuous or discrete • Qualitativenominal or ordinal

  8. Continuous predictor,Continuous response: • Q: is there a correlation between two numeric variables? • CorrelationSimple linear regression

  9. Continuous predictor,Nominal response: • Q: Does probability of the response change across the numeric predictor? • Logistic regression(which yields a chi-square statistic)

  10. Nominal predictor (independent groups),Continuous response: • Q: is there a mean difference between the groups? • For two groups: a t-test • For more than two groups: ANOVA • Followed by a multiple comparison procedure.

  11. Nominal predictor (independent groups),Nominal response: • Q: is there an association between two nominal variables? • Q: is the % on one variable different across the groups of the other variable? • Chi-square, orFisher’s exact p-value

  12. Nominal predictor (paired occasions or measures),Nominal response: • Q: is there a mean change across time? • Q: is there a difference between two paired measures? • Two: paired t-test • More than two: repeated-measuresANOVA

  13. Nominal predictor (paired occasions or measures),Nominal response: • Q: Are paired nominal outcomes different? • McNemar’s chi-square

  14. Time to an event: A response occurs (event) at a time point • Q: Is the survival time different between groups? • Kaplan-Meier survival analysis • Example: do crowns or amalgams last longer?

  15. What’s the question? • Usually, questions are of the form: • For ___ response variable, is there a relationship with ___ predictor variable? • For ___ response variable, is there a difference between the groups identified by the ___ predictor variable? • Sometimes, you want to conclude “no difference” or “just as good as”. • These require different tests: Equivalence tests.

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