Test Wizard

What do you want to evaluate?


Differences

Is your outcome categorical or continuous
Categorical
Continuous

Differences / Categorical outcomes

Do you want to compare 2 or more groups/variables or compare the mean/median of 1 variable to a population value/0?
2 or more groups
1 group

Differences / Categorical outcomes / 2 or more groups

For independent variables/outcomes (default) use:
Pearson's chi-squared test.

Use the Fisher's exact test instead if any outcome has less then 10 counts.

For dependent variables/outcomes (clustered dat) use:
McNemar's test


Differences / Categorical outcomes / 1 group

You can use:
Binomial or Chi-squared goodness of fit test.


Differences / Continuous outcomes

Do you want to compare 2 or more groups/Variables or compare the mean/median of 1 variable to a population value/0?

Differences / Continuous outcomes / 2 groups

Are the groups unrelated (independent/non-clustered data)?

Differences / Continuous outcomes / 2 groups / Independent

For normally distributeed outcome (default) use:
2-sample Student's t-test.

For non-normally distributeed outcome use:
Wilcoxon rank-sum test (a.k.a Mann-Whitney U test).


Differences / Continuous outcomes / 2 groups / Dependent

For normally distributeed outcome (default) use:
Paired Student's t-test.

For non-normally distributeed outcome use:
Wilcoxon signed-rank test.


Differences / Continuous outcomes / >2 groups

For normally distributeed outcome (default) use:
One-way ANOVA.

For non-normally distributeed outcome use:
Kruskal-Wallis test.

NB: performing an analysis on more than 2 groups of dependent continuous data usually entails a repeated-measurement analysis on so-called longitudinal data. This either requires separate comparisons of each 2-time points or a complex type of analysis such as linear mixed effects regression modelling (learn more in the GCR academy).


Differences / Continuous outcomes / 1 group

For normally distributeed outcome (default) use:
1-sample Student's t-test.

For non-normally distributeed outcome use:
Sign test.


Association-Correlation

Are both variables dichotomous/categorical or continuous?

Association-Correlation / Categorical

You can use:
Pearson's chi-square test

Use Fisher's exact test if any of the outcomes has less then 10 counts.

You can also use:
Logistic regression analysis


Association-Correlation / Continuous

You can use:
Pearson's correlation coefficient

You can also use:
Simple linear regression analysis

NB: use this approach to evaluate whether two different variables are correlated. Evaluating the agreement/reliability between two similar variables requires a different approach.


Prediction

What is the nature of the outcome that you want to predict?

Prediction / Categorical

You can use:
Logistic regression analysis


Prediction / Continuous

You can use:
Linear regression analysis


Prediction / Survival

For a univariable or descriptive analysis use:
Kaplan-Meier analysis +/- Log-rank test

For a multivariable prediction model use:
Cox Proportional-Hazards model


Agreement-reliability

What is the nature of the outcome that you want to predict?

Nominal variables are unranked categorical, ordinal variables are ranked categorical.


Agreement-reliability / Nominal

For agreement use:
Proportions of (specific) agreement

For reliability use:
Cohen's kappa


Agreement-reliability / Nominal

For agreement use:
Proportions of (specific) agreement

For reliability use:
Cohen's kappa

NB: Reproducibility is the umbrella term for agreement and reliability.

Agreement is an evaluation of the measurement error (number of cases with agreement/number of total cases).
It answers the question: How close are scores for repeated measurements?

Reliability is an evaluation of discriminatory ability (measure of agreement corrected for agreement by chance).
It answers the question: How well can patients be distinguished from each other despite measurement error?

See the reproducibility research page in the study design aid for more info.


Agreement-reliability / Ordinal

For agreement use:
Proportions of (specific) agreement

For reliability use:
Ranked intraclass correlation
Matrix of kappa coefficients
Weighted kappa

NB: Reproducibility is the umbrella term for agreement and reliability.

Agreement is an evaluation of the measurement error (number of cases with agreement/number of total cases).
It answers the question: How close are scores for repeated measurements?

Reliability is an evaluation of discriminatory ability (measure of agreement corrected for agreement by chance).
It answers the question: How well can patients be distinguished from each other despite measurement error?

See the reproducibility research page in the study design aid for more info.


Agreement-reliability / Continuous

For agreement use:
Bland-Altman plot with bias and 95% limits of agreement Standard error of measurement
Coefficients of variation

For reliability use:
Intraclass correlation coefficients

NB: Reproducibility is the umbrella term for agreement and reliability.

Agreement is an evaluation of the measurement error (number of cases with agreement/number of total cases).
It answers the question: How close are scores for repeated measurements?

Reliability is an evaluation of discriminatory ability (measure of agreement corrected for agreement by chance).
It answers the question: How well can patients be distinguished from each other despite measurement error?

See the reproducibility research page in the study design aid for more info.