Multilevel and Longitudinal Modeling Using Stata

4,527 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Financial support and practical help between older parents and their middle-aged children in Europe (2010, methodology): “As we were interested in the effects of contextual structures on the likelihood of transfers, controlling for the composition of a country in terms of opportunities, needs and family structures, we estimated multivariate logistic random intercept models using the Stata module GLLAMM (Rabe-Hesketh an”
The Effects of Financial Development on Foreign Direct Investment (2014, neutral): “This financial development measure, using unit-level data (Rabe-Hesketh and Skrondal, 2012).”
Rose effect and the euro: is the magic gone? (2010, neutral): “Since the pioneering work of Rose (2000) and his result that currency unions increase trade by more than 200%, a whole new stream of literature has emerged and thrived, focusing especially on the Eurozone in recent years.”
Prediction in multilevel generalized linear models (2009, methodology): “These estimates were obtained using gllamm (e.g. Rabe-Hesketh and Skrondal (2008b)) Table 1.”
Perceived progress variability and entrepreneurial effort intensity: The moderating role of venture goal commitment (2015, methodology): “We also included the cluster or group mean of perceived progress (i.e., the between-person perceived progress), which is the instrumental variable that is correlated with person-mean centered progress but not correlated with the random intercept (cf. Rabe-Hesketh and Skrondal, 2005).”