Question at position 19 Cause-and-Effect Models can have multiple independent variables.TrueFalse

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The question presents a statement about Cause-and-Effect Models and asks whether it can have multiple independent variables. 
Option 1: 'True' — This could be correct because in many cause-and-effect or experimental designs, researchers manipulate or account for more than one independent variable to observe their separate or combined effects on the dependent variable. Multiple independent variables allow for more complex designs such as factorial experiments, where interactions between factors can be explored. 
Option 2: 'False' — This would be incorrect if one assumes that a cause-and-effect model is restricted to exactly one cause. In practice, many causal models include several independent variables to capture different potential causes or to control for confounding factors, enabling a clearer estimate of each variable’s unique impact. Saying it can never have multiple independent variables would ignore common experimental and quasi-experimental practices. 
Thus, evaluating the statement requires recognizing that a cause-and-effect framework does not inherently limit the model to a single independent variable; instead, it often accommodates multiple factors, sometimes with interactions, though complexity and interpretation increase with more variables. The core idea is about causal influence, not the immutability of a single predictor, so the presence of multiple independent variables is compatible with many causal analyses.

Question at position 19 Cause-and-Effect Models can have multiple independent variables.TrueFalse

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