Simple Interactive Statistical Analysis
Explanation.
Provides more easy input for SISA procedures which do two by two table analysis. It concerns the following procedures:
This procedure concerns three webpages which follow on one another.
- Data specification and input
- Copy of the procedure input page
- Results of the analysis
Input.
The procedure dichotomizes cases/persons/measurements/respondents in a two variable dataset into a two by two table which can be used in various SISA procedures. The data in the first column concerning the first variable are dichotomized over the table rows while the data in the second column concerning the second variable are dichotomized over the table columns. For the t-test it is considered that the data in the first column "explains" the data in the second column.
The data can be copied for example from a spreadsheet or word processor or the data can be typed in manually into the "Input data here:" field. The numbers in the input field have to be separated by spaces, or returns, or semicolons, or colons, or tabs, but can NOT be separated by comma’s or full stops. The data in the input field is read row wise, so first the data in the first row followed by the second, the third and all the other rows.
Limitations.
The formatting and tabulating of large datasets might take a while in which case there might be warnings, just select "continue" and in the end the computer will get there. Cases with unknown characters in the values are skipped, unknown are all non numerical characters except for the separator characters mentioned above. Information on the number of cases read and the number of invalid cases can be found in the address bar in the top of your browser.
Example of input:
1 252 28
2 33
1 24
2 25
1 22
2 34
2 25
. 25
2 21
1 28
1 27
2 25
2 21
2 34
A 15 cases two variables in two columns data set is shown above. It concerns an indicator (factor) variable in the first column indicating males with the value 1 and females with the value 2. For one case the gender is missing. BMI is the dependent variable in the second column. We dichotomize BMI into normal weight, BMI less then 25, and overweight, BMI 25 and above. After pasting the data into the input box and setting the appropriate values in the values boxes, in the top box the default of 2 is correct and in the second box we fill in the value 25. After hitting the "make table" button the program returns the table shown below:
|
V2<25 |
V2>=25 |
V1<2 |
2 |
3 |
V1>=2 |
2 |
7 |
Two males (i.e. V1<2) and two females (V1>=2) have a BMI below 25 (V2<25), three males and seven females have a BMI of 25 or above (V2>=25). The t-test shows that 40% (u1=0.4*100) of the males are normal weigth, against 22.2% (u2=0.22*100) of the females.
The address bar shows that the program read 15 cases of which the one without the respondent's gender was invalid,
i.e.: "......Copy.php?n11=2&n12=3&n21=2&n22=7&RowSplit=2.00&ColSplit=25&read=15&invalid=1"
