Logistic Regression Results Report Template
Analysis Settings
The logistic regression analysis was conducted in SmartPLS 4. The dependent variable was [binary dependent variable], coded as [0 = ...] and [1 = ...]. The independent variables were [list predictors]. The model was estimated using maximum likelihood estimation with [default/custom] maximum iterations and stopping criterion. Statistical significance was assessed using [two-tailed/one-tailed] tests at the [0.05] significance level.
Model Fit
| Fit Criterion | Null Model | Estimated Model | Interpretation |
|---|---|---|---|
| Log-likelihood | |||
| Deviance | |||
| AIC | |||
| BIC |
The estimated model showed [better/weaker] fit than the null model because [deviance/AIC/BIC] was [lower/higher].
Pseudo R-Square
| Measure | Value | Interpretation |
|---|---|---|
| McFadden's R-square | ||
| Cox and Snell's R-square | ||
| Nagelkerke's R-square |
Confusion Matrix
| Classification Result | Value |
|---|---|
| Correctly classified 0 group | |
| Correctly classified 1 group | |
| Overall classification accuracy |
Logistic Coefficients
| Predictor | Coefficient | Wald | p | Odds Ratio | Decision |
|---|---|---|---|---|---|
| X6 | |||||
| X7 | |||||
| X8 | |||||
| X9 | |||||
| X10 | |||||
| X11 | |||||
| X12 | |||||
| X13 | |||||
| X14 | |||||
| X15 | |||||
| X16 | |||||
| X17 | |||||
| X18 |
Interpretation Paragraph
[Predictor] was a statistically significant predictor of group membership (b = ..., Wald = ..., p = ...). The coefficient was [positive/negative], indicating that higher values of [predictor] were associated with [higher/lower] log-odds of being in the group coded 1. The odds ratio was [...], meaning that a one-unit increase in [predictor] multiplied the odds by [...], holding the other predictors constant.
Reporting Warning
Do not interpret logistic coefficients as direct changes in probability. Coefficients are changes in log-odds. Use odds ratios or predicted probabilities for clearer communication.
Limitation Statement
The logistic model should be interpreted as a classification or association model unless the research design supports causal inference.