omitted variable bias

the situation in which values calculated from a statistical model systematically overestimate or underestimate a degree of relationship or other quantity of interest because an important variable has been left out of the model. For example, a researcher could hypothesize a linear regression equation in which stressful life events and lack of social support predict depression. If coping skills also are highly relevant to predicting depression, the researcher’s failure to include that element in his or her conceptualization would create an omitted variable bias. The exclusion of important variables from models may constrain the validity of study findings. See also biased estimator.

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Psychology term of the day

May 9th 2024

best fit

the theoretical pattern that best accounts for the relationships among variables in a data set. For example, a regression equation having the best fit to sample data is the one that minimizes differences between observed and predicted values. On a scatterplot, a line of best fit provides a visual depiction of this pattern, allowing extrapolation to values not part of the original data set. It is important to note that the best-fitting pattern is not necessarily the one that generated the observed data, as other patterns not considered may provide a superior fit.