The major difference is that Split File includes the missing values in the grouping/splitting variable, whereas Compare Means excludes missing values in the grouping variable. Note: This combination of Split File: Compare Groups with Descriptives is very similar to what you would get with the Compare Means procedure. The individuals with missing values for gender had a much smaller range of heights than did the males or females.On average, the males were taller than the females.The male heights tended to have a slightly larger standard deviation (spread) than the female heights.

The height of the tallest male was greater than the height of the tallest female.At a glance, we can quickly take note that in this sample: The '.' group contains cases with missing gender values and nonmissing height values. This table gives us a breakdown of how many observations were in each group (N), and the minimum, maximum, average, and standard deviation of each group. Double click on the HeightВ variable, then click OK. Select Analyze > Descriptive Statistics > Descriptives. Now let's view the aforementioned descriptive statistics for the variable Height with respect to Gender. Double-click the variable Gender to move it to the Groups Based on field.ДЄfter splitting the file, the only change you will see in the Data View is that data will be sorted in ascending order by the grouping variable(s) you selected.To split the data in a way that will facilitate group comparisons: If you choose to split your data using the Compare groups option and then run a statistical analysis in SPSS, your output will be displayed in a single table that organizes the results according to the grouping variable(s) you specified. We'll use both Split File methods so that we can compare what their outputs look like. Let's couple the Split File procedure with the Descriptives procedure to get summary statistics for the two groups. Suppose that we want to get a summary of the differences in height between males and females in the sample data. Do you want a single table with all results, or separate tables for each group's results? A good rule of thumb is to choose Compare Groups if you want to be able to directly compare the results of your groups, and to choose Organize Output by Groups if the information is from separate trials or samples (such as cohorts from different years). The choice of which splitting method to use is entirely about what format the user wants their results in. If Organize output by groups is used, then each groups' results will be put into a separate table.The table will have sections showing the results for each group. If Compare groups is used, then all of the results will be shown in a single table.The difference between the two options is how the numeric results are presented.

This is true regardless of what statistical analysis is used. The Compare and Organize options produce numerically identical results when the same grouping variable(s) are applied. What are the differences in the split file options?

Create dummy variables spss version 25