| # Choosing

Choosing a Statistical Method, with Automatic Internet Searching

Taken from ‘Outline for the Proposed JavaScript Open Source Version of StatCalc’

By Hemant Kulkarni, San Antonio November 18, 2002

The following tables outline the suggested matrix. Please remember that the suggested options are the ones that CAN be chosen in a given situation. These options do NOT HAVE to be chosen.

To do a search (with Google.com) if you have an Internet connection, click on an item within a table cell. If you click on empty space within a cell, the search may include ALL the items in the cell. After you see the results, you may want to add a word like ´method,´ ´calculator,´ ´equation,´ or ´tutorial´ to narrow the search.

1. DESCRIPTIVE STUDIES

Situation | Epidemiologic results | Statistical methods
Time description | Scatter plots Scatter plots with trend lines Scatter plots with spline smoothing | Seasonality index
Place description | Spot maps | Clustering methods like k-means
Person description | Bar charts Pie charts Histograms Box plots Box and whisker plots Stem and leaf diagrams Hierarchical trees Scatter plots | Mean Proportion Standard deviation Standard errors Median Percentiles Mode

2. CROSS-SECTIONAL STUDIES

Situation | Epidemiologic results | Statistical methods
Group comparison | Risk reduction with 95% confidence intervals Odds ratios with 95% confidence intervals | chi square test of association Fisher’s exact test Φ coefficient Cramer’s V chi square test for linear trend Student’s T test (unpaired) Mann-Whitney U test Mantel-Haenszel chi square test Unconditional multiple logistic regression Generalized linear models Bonferroni’s corrections

3. CASE-CONTROL STUDIES

Situation | Epidemiologic results | Statistical methods
Unmatched case-control study Single exposure variable expressed as Yes/No One set of controls | Odds ratio with 95% confidence interval Cornfield’s method Woolf’s method Exact method | chi square test of association Fisher’s exact test Φ coefficient
Unmatched case-control study Single exposure variable expressed as multiple, ordered categories One set of controls | Odds ratio for each category compared to the reference category with 95% confidence interval Cornfield’s method Woolf’s method Exact method | chi square test of association Fisher’s exact test Cramer’s V chi square test for linear trend
Unmatched case-control study Single continuous variable One set of controls | - | Student’s T test (unpaired) Mann-Whitney U test
Unmatched case-control study Multiple exposure variables expressed as Yes/No One set of controls | Odds ratio with 95% confidence interval for each variable separately Cornfield’s method Woolf’s method Exact method Adjusted ORs for combinations of variables Stratified and summary OR with 95% confidence interval | chi square test of association Fisher’s exact test Φ coefficient Unconditional multiple logistic regression Mantel-Haenszel chi square test
Unmatched case-control study Multiple exposure variables expressed as two or more, ordered categories One set of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately Cornfield’s method Woolf’s method Exact method Adjusted ORs for combinations of variable categories | chi square test of association Fisher’s exact test Cramer’s V chi square test for linear trend Unconditional multiple logistic regression
Unmatched case-control study Multiple continuous variables One set of controls | - | Student’s T test (unpaired) Mann-Whitney U test Unconditional multiple logistic regression
Unmatched case-control study Combinations of variable types One set of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately Cornfield’s method Woolf’s method Exact method Adjusted ORs for combinations of variable categories Stratified and summary OR with 95% confidence interval | chi square test of association Fisher’s exact test Φ coefficient Cramer’s V chi square test for linear trend Student’s T test (unpaired) Mann-Whitney U test Mantel-Haenszel chi square test Unconditional multiple logistic regression Generalized linear models
Unmatched case-control study Single exposure variable expressed as Yes/No Multiple sets of controls | Odds ratio with 95% confidence interval Cornfield’s method Woolf’s method Exact method Stratified and summary OR with 95% confidence interval | chi square test of association Fisher’s exact test Φ coefficient Mantel-Haenszel chi square test
Unmatched case-control study Single exposure variable expressed as multiple, ordered categories Multiple sets of controls | Odds ratio for each category compared to the reference category with 95% confidence interval Cornfield’s method Woolf’s method Exact method For each set of controls separately | chi square test of association Fisher’s exact test Cramer’s V chi square test for linear trend Bonferroni’s correction for multiple comparisons
Unmatched case-control study Single continuous variable Multiple sets of controls | - | Analysis of variance with Tukey’s pairwise comparison tests Kruskal-Wallis test with Mann-Whitney test for pairwise comparisons after Bonferroni correction
Unmatched case-control study Multiple exposure variables expressed as Yes/No Multiple sets of controls | Odds ratio with 95% confidence interval for each variable separately Cornfield’s method Woolf’s method Exact method Adjusted ORs for combinations of variables Stratified and summary OR with 95% confidence interval | chi square test of association Fisher’s exact test Φ coefficient Mantel-Haenszel test Unconditional multiple logistic regression
Unmatched case-control study Multiple exposure variables expressed as two or more, ordered categories Multiple sets of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately Cornfield’s method Woolf’s method Exact method Adjusted ORs for combinations of variable categories | chi square test of heterogeneity Fisher’s exact test Cramer’s V chi square test for linear trend Unconditional multiple logistic regression
Unmatched case-control study Multiple continuous variables Multiple sets of controls | - | Analysis of variance with Tukey’s pairwise comparison tests Kruskal-Wallis test with Mann-Whitney test for pairwise comparisons after Bonferroni correction Polytomous multiple logistic regression
Unmatched case-control study Combinations of variable types Multiple sets of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately Cornfield’s method Woolf’s method Exact method Adjusted ORs for combinations of variable categories Stratified and summary ORs | chi square test of association Fisher’s exact test Φ coefficient Cramer’s V chi square test for linear trend Student’s T test (unpaired) Mann-Whitney U test Unconditional multiple logistic regression Analysis of variance and Tukey’s pairwise comparisons Kruskal-Wallis test Generalized linear models
Matched case-control study Single exposure variable expressed as Yes/No One set of controls | Odds ratio with 95% confidence interval · McNemar’s method | McNemar’s chi square test of association
Matched case-control study Single exposure variable expressed as multiple, ordered categories One set of controls | Odds ratio for each category compared to the reference category with 95% confidence interval by collapsing into 2X2 tables McNemar’s method | McNemar’s chi square test of association Breslow-Day test
Matched case-control study Single continuous variable One set of controls | - | Student’s T test (paired) Wilcoxon signed-rank test
Matched case-control study Multiple exposure variables expressed as Yes/No One set of controls | Odds ratio with 95% confidence interval for each variable separately McNemar’s Method Adjusted ORs for combinations of variables | McNemar’s chi square test of association Conditional multiple logistic regression
Matched case-control study Multiple exposure variables expressed as two or more, ordered categories One set of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately McNemar’s method Adjusted ORs for combinations of variable categories | McNemar’s chi square test of association Breslow-Day test Conditional multiple logistic regression
Matched case-control study Multiple continuous variables One set of controls | - | Student’s T test (paired) Wilcoxon signed- rank test Conditional multiple logistic regression
Matched case-control study Combinations of variable types One set of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately McNemar’s method Adjusted ORs for combinations of variable categories | McNemar’s chi square test of association Breslow-Day test Student’s T test (paired) Wilcoxon signed-rank test Conditional multiple logistic regression Generalized linear models
Matched case-control study Single exposure variable expressed as Yes/No Multiple sets of controls | Odds ratio with 95% confidence interval McNemar’s method Stratified and summary OR with 95% confidence interval | McNemar’s chi square test of association Mantel-Haenszel chi square test
Matched case-control study Single exposure variable expressed as multiple, ordered categories Multiple sets of controls | Odds ratio for each category compared to the reference category with 95% confidence interval by collapsing into 2X2 tables McNemar’s method For each set of controls separately | McNemar’s chi square test of association Breslow-Day test Bonferroni’s correction for multiple comparisons
Matched case-control study Single continuous variable Multiple set of controls | - | Friedman’s Analysis of variance Kruskal-Wallis test with Mann-Whitney test for pairwise comparisons after Bonferroni correction
Matched case-control study Multiple exposure variables expressed as Yes/No Multiple sets of controls | Odds ratio with 95% confidence interval for each variable separately McNemar’s method Adjusted ORs for combinations of variables Stratified and summary OR with 95% confidence interval | McNemar’s chi square test of association Mantel-Haenszel test Conditional multiple logistic regression
Matched case-control study Multiple exposure variables expressed as two or more, ordered categories Multiple sets of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately McNemar’s method Adjusted ORs for combinations of variable categories | chi square test of heterogeneity Breslow-Day test Conditional multiple logistic regression
Matched case-control study Multiple continuous variables Multiple sets of controls | - | Friedman’s Analysis of variance Kruskal-Wallis test with Mann-Whitney test for pairwise comparisons after Bonferroni correction Polytomous multiple logistic regression
Matched case-control study Combinations of variable types Multiple sets of controls | Odds ratio for each category compared to the reference category with 95% confidence interval for each variable separately McNemar’s method Adjusted ORs for combinations of variable categories Stratified and summary ORs | McNemar’s chi square test of association Breslow-Day test Student’s T test (paired) Wilcoxon’s signed-rank test Conditional multiple logistic regression Friedman’s Analysis of variance Kruskal-Wallis test Mantel-Haenszel test Generalized linear models

4. COHORT STUDIES

Situation | Epidemiologic results | Statistical methods
Outcome is number of events in the exposed and unexposed groups where the event can occur only once in a single individual | Relative risk with 95% confidence interval Excess fraction (also called as risk reduction) Etiologic fraction (also called attributable risk) Population attributable risk Population attributable risk proportion | chi square test of association Fisher’s exact test Φ coefficient chi square test of linear trend for multiple ordered categorical variables Unconditional multiple logistic regression Generalized linear models
Outcome is number of events in the exposed and unexposed groups where the event can occur multiple times in a single individual | Relative hazards and their 95% confidence interval | Kaplan-Meier survival curves Log-rank test OR Wilcoxon test based on the violation of proportional hazards assumption Cox proportional hazards model Poisson’s multiple regression
Outcome is time to events in the exposed and unexposed groups | Relative hazards and their 95% confidence intervals | Kaplan-Meier survival curves Log-rank test OR Wilcoxon test based on the violation of proportional hazards assumption Cox proportional hazards model
Outcome is a continuous variable for the exposed and unexposed groups | Relative risks and their 95% confidence intervals using clinically meaningful cut-offs | chi square test of association Fisher’s exact test Φ coefficient chi square test of linear trend for multiple ordered categorical variables Unconditional multiple logistic regression Generalized linear models Time series analyses

5. CLINICAL AND PREVENTIVE TRIALS

Situation | Epidemiologic results | Statistical methods
Outcome is number of events in the exposed and unexposed groups where the event can occur only once in a single individual | Relative risk with 95% confidence interval Excess fraction (also called as risk reduction) Etiologic fraction (also called attributable risk) Number needed to treat (NNT) Vaccine efficacy with its 95% confidence interval | chi square test of association Fisher’s exact test Φ coefficient chi square test of linear trend for multiple ordered categorical variables Unconditional multiple logistic regression Generalized linear models
Outcome is number of events in the exposed and unexposed groups where the event can occur multiple times in a single individual | Relative hazards and their 95% confidence interval Vaccine efficacy with 95% confidence interval | Kaplan-Meier survival curves Log-rank test OR Wilcoxon test based on the violation of proportional hazards assumption Cox proportional hazards model Poisson’s multiple regression Sequential trial with interim analyses using the alpha-spending function Generalized linear models
Outcome is time to events in the exposed and unexposed groups | Relative hazards and their 95% confidence intervals Vaccine efficacy and its 95% confidence interval | Kaplan-Meier survival curves Log-rank test OR Wilcoxon test based on the violation of proportional hazards assumption Cox proportional hazards model
Outcome is a continuous variable for the exposed and unexposed groups | Relative risks and their 95% confidence intervals using clinically meaningful cut-offs | chi square test of association Fisher’s exact test Φ coefficient chi square test of linear trend for multiple ordered categorical variables Unconditional multiple logistic regression Generalized linear models Time series analyses

6. SCREENING TEST PERFORMANCE EVALUATION

Situation | Epidemiologic results | Statistical methods
Dichotomous (Positive/Negative) result compared with a reference standard | Sensitivity Specificity Positive predictivity Negative predictivity Accuracy Likelihood ratio of a positive test Likelihood ratio of a negative test Cohen’s kappa Entropy Bias index | chi square test of association Fisher’s exact test Φ coefficient
Multiple categorical test outcome compared with a reference standard | Likelihood ratios for each categorical test outcome Receiver-operating characteristic curve | chi square test of association Fisher’s exact test Φ coefficient chi square test of linear trend Area under the ROC curve and its 95% confidence interval by Wilcoxon’s method
Continuous test outcome compared with a reference standard | Likelihood ratios for pre-defined categories of the outcome Receiver operating characteristic curve | Area under the ROC curve and its 95% confidence interval Optimum operating point (OOP) choosing Cost-of-error comparisons