Basic Statistics and Data Analysis

Lecture notes, MCQS of Statistics

Binary Logistic Regression Minitab Tutorial

Binary Logistic Regression Minitab Tutorial

Binary Logistic Regression is used to perform logistic regression on a binary response (dependent) variable (a variable only that has two possible values, such as presence or absence of a particular disease, this kind of variable is known as dichotomous variable i.e binary in nature).

Binary Logistic Regression can classify observations into one of two categories. These classifications can give fewer classification errors than discriminant analysis for some cases.

The default model contains the variables that you enter in Continuous predictors and Categorical predictors. You can also add interaction and/or polynomial terms by using the tools available in model sub-dialog box.

Minitab stores the last model that you fit for each response variable. This stored models can be used to quickly generate predictions, contour plots, surface plots, overlaid contour plots, factorial plots, and optimized responses.

To perform a Binary Logistic Regression Analysis in Minitab, follow the steps given below. It is assumed that you have already launched the Minitab software.

Step1:  Choose Stat > Regression > Binary Logistic Regression > Fit Binary Logistic Model.

Fit Binary Logistic Regression

Fit Binary Logistic Regression

Step2:  Do one of the following:

If your data is in raw or frequency form, follow these steps:

Response in Binary Logistic Regression (Frequency Format)

Response in Binary Logistic Regression (Frequency Format)

  1. Choose Response in binary response/frequency format, from combobox on top
  2. In Response text box, enter the column that contains the response variable.
  3. In Frequency text box, enter the optional column that contains the count or frequency variable.

If you have summarized data, then follow these steps:

Response in Binary Logistic Regression (Trial Format)

Response in Binary Logistic Regression (Trial Format)

  1. Choose Response in event/trial format, from combobox on top of the dialog box.
  2. In Number of events, enter the column that contains the number of times the event occurred in your sample at each combination of the predictor values.
  3. In Number of trials, enter the column that contains the corresponding number of trials.

Step4:  In Continuous predictors, enter the columns that contain continuous predictors. In Categorical predictors, enter the columns that contain categorical predictors. You can add interactions and other higher order terms to the model.

Step5:  If you like, use one or more of the dialog box options, then click OK.

The following are options available in the main dialog box of Minitab Binary Logistic Regression:

Response in binary response/frequency format: Choose if the response data has been entered as a column that contains 2 distinct values i.e as a dichotomous variable.
Response: Enter the column that contains the response values.
Response event: Choose which event of interest the results of the analysis will describe.
Frequency (optional): If the data are in two columns i.e. one column that contains the response values and the other column that contains their frequencies then enter the column that contains the frequencies.
Response in event/trial format: Choose if the response data are two columns – one column that contains the number of successes or events of interest and one column that contains the number of trials.
Event name: Enter a name for the event in the data.
Number of events: Enter the column that contains the number of events.
Number of trials: Enter the column that contains the number of nonevents.
Continuous predictors: Select the continuous variables that explain changes in the response. The predictor is also called the X variable.
Categorical predictors: Select the categorical classifications or group assignments, such as type of raw material, that explain changes in the response. The predictor is also called the X variable.

Step 6: To stores diagnostic measures and characteristics of the estimated equation click Storage… button.

Binary Logistic Regression Storage Dialog Box

Binary Logistic Regression Storage Dialog Box

 

Download Binary Logistic Regression Minitab Tutorial PDF File

 

The Author

Muhammad Imdadullah

Student and Instructor of Statistics and business mathematics.
Currently Ph.D. Scholar (Statistics), Bahauddin Zakariya University Multan.

Like Applied Statistics and Mathematics and Statistical Computing.
Statistical and Mathematical software used are: SAS, STATA, GRETL, EVIEWS, R, SPSS, VBA in MS-Excel.

Like to use type-setting LaTeX for composing Articles, thesis etc.

4 Comments

Add a Comment
  1. insightful posts, thank you.

  2. Krishna Pokharel

    Hello Muhammad,
    I want to store the coefficients and variance-covariance matrix of the parameter estimates for binary logit in Minitab 17. When I clicked these options, only coefficients are stored on Worksheet?
    Where does var-covar matrix store?
    (ii) How can I change a starting value?
    (iii) Can I change algorithm and convergence level?
    I hope you can help me.
    Thanks,
    Krishna
    USA

    1. Minitab save vectors or variable in data sheet while matrices in matrix format which is hidden (not display in data sheet).

      To see a stored matrix or even a variable click DATA –> Display Data and select the required variable or matrix. Note that by default matrix names starts with M1.

      Could not understand option (ii) and (iii)

      Keep visiting the site.

      Thanks

  3. please can you post an example of logistic regression,because i want to know how can i analyse the data shown by minitab

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