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A confounder is a variable that influences the relationship between the experimental variables. To gain clear vision that influence must be held constant or neutralized.

Variables can be of several kinds. Most well known are the experimental variables, consisting of one or more independent variables and one or more dependent variables, and non-experimental variables.

A confounder is a variable that covariates with the experimental variables. A confounder is always disturbing the relationship of interest. Therefore it always needs to be controlled for.

It depends on which relations are being researched and how confounders influence the relationship. It can have a mediation effect, a moderating effect or it might be a cause for multicollinearity.

The best way to deal with a confounder is statistical. In an ANOVA it can be treated as a covariate - this changes the name to ANCOVA - or as a control variable in regression analysis, which changes the name to hierarchical regression.

Related terms to confounder:

• Experimental variables
• Control variables
• Nominal data
• Ordinal data
• Interval data
• Ratio data

• Correlation
• Regression
• Hierarchical regression
• Mediation
• Moderation

All these tests are clearly explained in in our SPSS-tutorials.

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