that is called the beta weight, regression weight or weighted regression coefficients (denoted βW or BW). The prediction is obtained by adding these products along with a constant. When the weights are chosen to give the best prediction by some criterion, the model referred to as a proper linear model. Therefore, multiple regression is a proper linear model. By contrast, unit-weighted regression is called an improper linear model. Model specification Standard multiple regression hinges on the assumption that all relevant predictors of the outcome are included in the regression model. This assumption is called model specification. A model is said to be specified when all relevant predictors are included in the model, and all irrelevant predictors are excluded from the model. In practical settings, it is rare for a study to be able to determine all relevant predictors a priori. In this case, models are not specified and the estimates for the beta weights suffer from omitted variable bias. That is, the beta weights may change from one sample to the next, a situation sometimes called the problem of the bouncing betas. It is this problem with bouncing betas that makes unit-weighted regression a useful method. See also Linear regression Regression analysis Robust regression References Bobko, P., Roth, P. L., & Buster, M. A. (2007). "The usefulness of unit weights in creating composite scores: A literature review, application to content validity, and meta-analysis". Organizational Research Methods, volume 10, pages 689-709. Burgess, E. W. (1928). "Factors determining success or failure on parole". In A. A. Bruce (Ed.), The Workings of the Indeterminate Sentence Law and Parole in Illinois (pp. 205–249). Springfield, Illinois: Illinois State Parole Board. Google books Cohen, Jacob. (1990). "Things I have learned (so far)". American Psychologist, volume 45, pages 1304-1312. Dawes, Robyn M. (1979). "The robust beauty of improper linear models in decision making". American Psychologist, volume 34, pages 571-582. . archived pdf Gottfredson, D. M., & Snyder, H. N. (July 2005). The mathematics of risk classification: Changing data into valid instruments for juvenile courts. Pittsburgh, Penn.: National Center for Juvenile Justice. NCJ 209158. Eric.ed.gov pdf Kerby, Dave S. (2003). "CART analysis with unit-weighted regression to predict suicidal ideation from Big Five traits". Personality and Individual Differences, volume 35, pages 249-261. Schmidt, Frank L. (1971). "The relative efficiency of regression and simple unit predictor weights in applied differential psychology". Educational and Psychological Measurement, volume 31, pages 699-714. Wainer,