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In experiments utilizing both manipulated and non-manipulated independent variables, causal conclusions can only be drawn concerning the manipulated factor. Because researchers do not systematically control or randomly assign participants to conditions of a non-manipulated variable (such as a personality trait), any observed effects might be the result of an unmeasured third variable. Consequently, findings related to the non-manipulated variable are strictly correlational.

Causal Limitations of Non-Manipulated Variables

The study by Schnall and colleagues illustrates the causal limitations of non-manipulated variables. While researchers could conclude that the manipulated variable of disgust affected the harshness of moral judgments, they could not make the same causal claim about private body consciousness. Because private body consciousness was only measured and not manipulated, any association with moral judgments might be caused by an unmeasured third variable, such as neuroticism, that independently increases both bodily awareness and moral strictness.

Example of Causal Limitations: Private Body Consciousness and Moral Judgments

Because non-experimental factorial designs rely entirely on measured rather than manipulated variables, researchers must be extremely cautious about inferring causality due to the directionality and third-variable problems. For example, in a non-experimental study linking participants' measured moods to their willingness to have unprotected sex, one cannot definitively claim that mood causes the risk-taking behavior. The observed effect on sexual willingness might instead be caused by an unmeasured third variable that happens to be correlated with the participants' moods.

Example of Causal Limitations in a Non-Experimental Factorial Design

Why are findings related to a non-manipulated independent variable, such as a personality trait, considered strictly correlational even when included in an experimental study?

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