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Shruthi Sundararaman
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  • Comparative or Predictive Study? Comparative (e.g. difference in blood pressure among groups of patients with different diseases). Predictive (e.g. what is the effect of x on y).
  • Comparing what? Means. Proportions.
  • Dependent or independent samples? Dependent samples (e.g. studying one group of patients before and after a treatment). Independent samples (e.g. comparing different groups of patients).
  • How many treatments? Two treatments. Three or more treatments.
  • T-test on two paired samples.
  • Repeated measures ANOVA, mixed models.
  • How many treatments? Two treatments. Three or more treatments.
  • Parametric or non-parametric? Parametric. Non parametric.
  • F-test or t-test on two independent samples.
  • Paired or independent samples? Paired samples. Independent samples.
  • Wilcoxon rank sums test.
  • Mann-whitney U test.
  • Parametric or non parametric? Parametric. Non parametric.
  • ANOVA (if significant, then do SNK, Sheffe's, Tukey's, or Bonferroni's.
  • Paired or independent samples? Paired. Independent.
  • Friedman test.
  • Kruksal-wallis test (if significant do a Dunn's test).
  • Comparing what proportions? Observed proportion and theoretical proportion. Two observed proportions. Multiple observed proportions to multiple theoretical proportions.
  • Test for one proportion (chi squared).
  • Chi squared test.
  • Multinomial goodness of fit test.
  • Dependent or independent relationship? Dependent (e.g. x predicts y). Independent (e.g. x and y are correlated).
  • Continuous or categorical predictor variable? Continuous (e.g. blood pressure). Categorical (e.g. blood type).
  • Chi squared test.
  • Continuous or binary outcome variable? Continuous (e.g. heart rate). Categorical (e.g. benign vs. malignant).
  • Linear regression.
  • Logistic regression.
  • Parametric or non-parametric? Parametric. Non-parametric.
  • Correlation coefficient.
  • Spearman's rank correlation.

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