השוואת שיטות

	ניתוח סדרות עתיות מופרעות (Interrupted Time Series - ITS)	רגרסיית ריבועים פחותים רגילים (OLS)
תחום	הסקה סיבתית	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	2002	2019
הוגה השיטה	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)	Wooldridge (textbook treatment); classical least squares
סוג	Quasi-experimental segmented regression	Linear regression
מקור מכונן	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.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
כינויים	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
קשורות	5	5
תקציר	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.	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).