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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Análise de Séries Temporais Interrompidas (ITS)×Regressão por Mínimos Quadrados Ordinários (MQO)×
ÁreaInferência causalEconometria
FamíliaRegression modelRegression model
Ano de origem20022019
Autor originalWagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)Wooldridge (textbook treatment); classical least squares
TipoQuasi-experimental segmented regressionLinear regression
Fonte seminalBernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Outros nomesITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analiziordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionados55
ResumoInterrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateComparar métodos: Interrupted Time Series · OLS Regression. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare