Comparar métodos

	Análise de Séries Temporais Interrompidas (ITS)	Pesquisa Longitudinal
Área	Inferência causal	Delineamento de pesquisa
Família	Regression model	Process / pipeline
Ano de origem	2002	Late 19th–early 20th century; methodologically codified through the 20th century
Autor original	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)	No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett
Tipo	Quasi-experimental segmented regression	Quantitative (or mixed) observational research design
Fonte seminal	Bernal, 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.	Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841
Outros nomes	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi	longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study
Relacionados	5	4
Resumo	Interrupted 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.	Longitudinal research is an observational design in which the same participants, groups, or units are measured repeatedly over an extended period. Rather than capturing a single snapshot, it tracks change, stability, and temporal sequencing of variables — making it the primary non-experimental strategy for studying development, growth, decline, and the unfolding of causal processes across time.