. . . . . . . . . . . . "Na estat\u00EDstica, a regress\u00E3o por stepwise \u00E9 um t\u00E9cnica de ajuste de modelos de regress\u00E3o em que a escolha das vari\u00E1veis preditivas \u00E9 realizada por um procedimento autom\u00E1tico. Em cada etapa, uma vari\u00E1vel \u00E9 considerada para adi\u00E7\u00E3o ou subtra\u00E7\u00E3o do conjunto de vari\u00E1veis explicativas com base em algum crit\u00E9rio pr\u00E9-especificado. Normalmente, se assume a forma de uma sequ\u00EAncia de testes ou t, mas outras t\u00E9cnicas s\u00E3o poss\u00EDveis, como R 2 ajustado, crit\u00E9rio de informa\u00E7\u00E3o de Akaike, crit\u00E9rio de informa\u00E7\u00E3o Bayesiano, Mallows, PRESS ou taxa de descoberta falsa. Na pr\u00E1tica frequente de ajuste do modelo final selecionado seguido de relat\u00F3rios de estimativas e intervalos de confian\u00E7a sem ajust\u00E1-los para levar em conta o processo de constru\u00E7\u00E3o de modelo levou a pedidos para parar de usar a constru\u00E7\u00E3o de modelo passo a passo ou pelo menos ter certeza de a incerteza do modelo \u00E9 refletida corretamente."@pt . . . . . . . . . . . . . . . . . . . . . . . . . "4877759"^^ . . . . . . . . . . . . . . . . . . . . . . "1080244859"^^ . . . . . "11877"^^ . . . . . . . . . . . . . "Na estat\u00EDstica, a regress\u00E3o por stepwise \u00E9 um t\u00E9cnica de ajuste de modelos de regress\u00E3o em que a escolha das vari\u00E1veis preditivas \u00E9 realizada por um procedimento autom\u00E1tico. Em cada etapa, uma vari\u00E1vel \u00E9 considerada para adi\u00E7\u00E3o ou subtra\u00E7\u00E3o do conjunto de vari\u00E1veis explicativas com base em algum crit\u00E9rio pr\u00E9-especificado. Normalmente, se assume a forma de uma sequ\u00EAncia de testes ou t, mas outras t\u00E9cnicas s\u00E3o poss\u00EDveis, como R 2 ajustado, crit\u00E9rio de informa\u00E7\u00E3o de Akaike, crit\u00E9rio de informa\u00E7\u00E3o Bayesiano, Mallows, PRESS ou taxa de descoberta falsa."@pt . . . . . . . . "Stepwise regression"@en . . . . . . . . . "In statistics, stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a forward, backward, or combined sequence of F-tests or t-tests."@en . . . . . . . . . "Regress\u00E3o por stepwise"@pt . . . . "In statistics, stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a forward, backward, or combined sequence of F-tests or t-tests. The frequent practice of fitting the final selected model followed by reporting estimates and confidence intervals without adjusting them to take the model building process into account has led to calls to stop using stepwise model building altogether or to at least make sure model uncertainty is correctly reflected.Alternatives include other model selection techniques, such as adjusted R2, Akaike information criterion, Bayesian information criterion, Mallows's Cp, PRESS, or false discovery rate."@en . . . . . . . .