The controls parameter
What it does
Columns held constant in a partial correlation, with the syntax of colFilter: "age", "age,income", "/^ctrl/".
A control is never taken as a variable, even when colFilter matches it: "*" with controls "age" correlates every other column, holding age constant.
Empty — no controls: the result is the Pearson correlation.
Each control takes one degree of freedom: df = n − 2 − k for k controls, so k controls need at least k + 3 complete rows; with fewer, Correlation, Significance and df are empty.
A constant control, or two controls that repeat each other (one a multiple of the other), leave Correlation and Significance empty on purpose: such a control carries no information and almost always means the wrong column was picked; a silent answer would hide that nothing was controlled for.
A row with a gap in any control is left out; in a matrix each pair also needs its two variables filled, so the pairs can rest on different rows (SPSS PARTIAL CORR by default uses one common sample).
Values
Optional.
In plain words
A teacher found that students who studied more hours got higher scores: of two students picked at random, the one who studied more scored higher in about 67 pairs out of 100. Older students did both, so she wrote age in controls. The correlation came out 0.36 among students of the same age: now the one who studied more scored higher in about 62 pairs out of 100, against 50 for a coin, weaker but still there. With age and income it compares students alike in both. Each control needs a few more full rows, and a control with the same number in every row leaves the cell empty, since it holds nothing to compare.
Where you use it
STATS_PARTIAL— Partial correlation: the Pearson correlation of two variables with the controls held constant (SPSS PARTIAL CORR). Two variables give one correlation, three or more a matrix, as STATS_PEARSON.
Examples
"age"— one control"age,income"— two controls
Get it in your sheet
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