2015
DOI: 10.32614/rj-2015-016
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Estimability Tools for Package Developers

Abstract: When a linear model is rank-deficient, then predictions based on that model become questionable because not all predictions are uniquely estimable. However, some of them are, and the estimability package provides tools that package developers can use to tell which is which. With the use of these tools, a model object's predict method could return estimable predictions as-is while flagging non-estimable ones in some way, so that the user can know which predictions to believe. The estimability package also provi… Show more

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Cited by 401 publications
(464 citation statements)
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“…1 were 10 Hz butterworth low-pass filtered for visual presentation. Statistical analyses were performed in R [48] using the ez [49], lsmeans [50], lmPerm [51], and signal packages [52]. …”
Section: Methodsmentioning
confidence: 99%
“…1 were 10 Hz butterworth low-pass filtered for visual presentation. Statistical analyses were performed in R [48] using the ez [49], lsmeans [50], lmPerm [51], and signal packages [52]. …”
Section: Methodsmentioning
confidence: 99%
“…Sample size was obtained by testing for one proportion using the software Java Applets for Power and Sample Size (Lenth, 2006-9). We assumed the frequency of PHA-L positive axon terminals labelled for presynaptic mGlu receptors to be 20% and a presumed lack of or occasional presence of receptors in these terminals to be 1%.…”
Section: Methodsmentioning
confidence: 99%
“…All statistical analyses were run in R version 3.2.1 using lm function, with post hoc analysis carried out using the lsmeans package29.…”
Section: Methodsmentioning
confidence: 99%