Binary Fitted Line Plotoverview how to example data see also
Binary Fitted Line PlotStat > Regression > Binary Fitted Line Plot
Use Binary Fitted Line Plot to perform logistic regression of a single predictor variable on a binary response variable. A binary variable only has two possible values, such as presence or absence of a particular disease. Binary Fitted Line Plot fits a model with one continuous predictor with an iterative reweighted least squares algorithm to obtain maximum likelihood estimates of the parameters [29].
Binary logistic regression can classify observations into one of two categories. The classifications can give fewer classification errors than discriminant analysis for some cases [10], [31].
Response in binary response/frequency format: Choose if the response data has been entered as raw data or as two columns- one containing the response values and one column containing their frequencies.
Response: Enter the column that contains the response values.
Response event: Choose which event the results describe.
Frequency (optional): If the data has been entered as two columns - one containing the response values and one column containing their frequencies - enter the column containing the frequencies in the text box.
Response in event/trial format: Choose if the response data are two columns - one containing the number of successes or events of interest and one column containing the number of trials.
Event name: Enter a name for the event that is in the Number of events column.
Number of events: Enter the column that contains the number of events.
Number of trials: Enter the column that contains the number of nonevents.
Predictor: Select the continuous variable that explains changes in the response. The predictor is also called the X variable.