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Multivariate regression is implemented using regression splines (RS).
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In practice, the DDD analysis is implemented using a regression framework.
In practice, the DD analysis is implemented using a regression framework.20 We estimate several unique model specification that take the general form of the following OLS model: {LPE}_{it}=a+{beta}_1{Treat}_{it}+{beta}_2mathit{operatorname{Re}}{form}_t+{beta}_3{Treat}_{it}ast mathit{operatorname{Re}}{form}_t+{varepsilon}_{it} (1).
Lastly, we estimate hazard models, implemented using logistic regression, to illustrate the relationship between a pregnancy scare and subsequent unintended pregnancy (Table 4).
For all outcomes except for antidepressant behavior in the non-depressed patients, analyses will be implemented using multiple regression models for clustered data to account for the nesting of patient-level observations within providers and, for longitudinally assessed outcomes, the nesting of repeated measures within patients.
Since data for testing of fathers and maternal carriers were sparse, we used exact logistic regression, but analyses implemented using ordinary logistic regression with robust standard errors gave consistent results.
implemented using the STATA11 regression 'xtreg, vie robust) fe'.
Computational methods, which can be implemented using standard Cox regression software, are given for fitting "exact" pseudolikehood estimates and robust and asymptotic variance estimators from case-cohort data.
These analyses of covariance were implemented using multivariable linear regression models.
It was implemented using the logistic regression algorithms in STATA 9.0 [ 11].
This will be implemented using multivariable linear regression, and will include in the model baseline number of visits and day of the week that tweeting activity started.
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