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42-Regression-logistic.Rmd
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42-Regression-logistic.Rmd
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# Logistic Regression {#logistic-regression}
#### How to perform a logistic regression in jamovi: {-}
1. You need one continuous predictor variable and one categorical (nominal or ordinal) outcome variable. Make sure that the measurement levels are set^[This is demonstrated in section \@ref(level-of-measurement).] so that the continuous variable is marked with <img src="images/icons/continuous.JPG" width="3%" alt=" the continuous data icon"/> and the grouping variable is marked with <img src="images/icons/nominal.JPG" width="3%" alt=" grouped data icon"/>.
A correct setup should look similar to this:
<img src="images/data_format/data_format_regression_logistic.JPG" width="25%"/>
2. Logistic regression can be found by selecting `Analyses` -> `Regression`. If the outcome variable is nominal (as in the above image), select `2 Outcomes` if it has 2 outcomes, or `N outcomes`if it has _more_ than 2 outcomes. If the outcome variable is ordinal (e.g. low, medium, high), select `Ordinal Outcomes`.
<img src="images/select/select_regression_logistic.JPG" width="40%"/>
3. Drag and drop your outcome variable to __Dependent Variable__ and your predictor to __Covariates__.
<img src="images/add_var/add_var_regression_logistic.JPG" width="70%"/>
4. The result is shown in the right panel:
<img src="images/output/output_regression_logistic.JPG" width="50%"/>