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ABSTRACT: Model formulas are the standard approach for specifying the variables in statistical models in the S language. Although being eminently useful in an extremely wide class of applications, they have certain limitations including being confined to single responses and not providing convenient support for processing formulas with multiple parts. The latter is relevant for models with two or more sets of variables, e.g., different equations for different model parameters (such as mean and dispersion), regressors and instruments in instrumental variable regressions, two-part models such as hurdle models, or alternative-specific and individual-specific variables in choice models among many others. The R package Formula addresses these two problems by providing a new class “Formula” (inheriting from “formula”) that accepts an additional formula operator | separating multiple parts and by allowing all formula operators (including the new |) on the left-hand side to support multiple responses.
Journal of Statistical Software. 01/2010;
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ABSTRACT: Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a package for R which intends to make the estimation of linear panel models straightforward. plm provides functions to estimate a wide variety of models and to make (robust) inference.
Journal of Statistical Software. 01/2008;
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ABSTRACT: We have analyzed the popularization activities undertaken by ten thousand CNRS researchers by means of their annual reports for the years 2004, 2005 and 2006. This is the first time that such an extensive statistical study on science popularization practices is carried out. Our main findings are : - the majority of researchers is not involved in popularization (51% has not done any popularization over the three-year period, two thirds have been involved in no more than one popularization action). - popularization practices are extremely diverse, both at the individual level (we have identified three subpopulations that feature distinctive attitudes towards popularization), and at the level of scientific disciplines (researchers in Humanities are twice as active as the average), as well as in laboratories or geographical regions. - the number of actions reported in 2005 greatly increased compared to 2004 (+ 26%), while they slightly diminished in 2006.
JCOM : Journal of Science Communication. 01/2007;
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ABSTRACT: We have analyzed the popularization activities undertaken by ten thousand CNRS researchers by means of their annual reports for the years 2004, 2005 and 2006. This is the first time that such an extensive statistical study on science popularization practices is carried out. Our main findings are : - the majority of researchers is not involved in popularization (51% has not done any popularization over the three-year period, two thirds have been involved in no more than one popularization action). - popularization practices are extremely diverse, both at the individual level (we have identified three subpopulations that feature distinctive attitudes towards popularization), and at the level of scientific disciplines (researchers in Humanities are twice as active as the average), as well as in laboratories or geographical regions. - the number of actions reported in 2005 greatly increased compared to 2004 (+ 26%), while they slightly diminished in 2006.
JCOM : Journal of Science Communication. 01/2007;
