One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer? The lmerTest package extends the 'lmerMod' class of the lme4 package, by overloading the anova and summary functions by providing p values for tests for fixed effects. We have implemented the Satterthwaite's method for approximating degrees of freedom for the t and F tests. We have also implemented the construction of Type I - III ANOVA tables. Furthermore, one may also obtain the summary as well as the anova table using the Kenward-Roger approximation for denominator degrees of freedom (based on the KRmodcomp function from the pbkrtest package). Some other convenient mixed model analysis tools such as a step method, that performs backward elimination of nonsignificant effects - both random and fixed, calculation of population means and multiple comparison tests together with plot facilities are provided by the package as well.

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lmerTest Package: Tests in Linear Mixed Effects Models

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Modern Applied Statistics With S

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

Extended-connectivity fingerprints (ECFPs) are a novel class of topological fingerprints for molecular characterization. Historically, topological fingerprints were developed for substructure and similarity searching. ECFPs were developed specifically for structure−activity modeling. ECFPs are circular fingerprints with a number of useful qualities: they can be very rapidly calculated; they are not predefined and can represent an essentially infinite number of different molecular features (including stereochemical information); their features represent the presence of particular substructures, allowing easier interpretation of analysis results; and the ECFP algorithm can be tailored to generate different types of circular fingerprints, optimized for different uses. While the use of ECFPs has been widely adopted and validated, a description of their implementation has not previously been presented in the literature.

Extended-Connectivity Fingerprints

The measurement of meaning

Preface. 1. Introduction. 2. The Completely Randomized Design. 3. The Randomized Block Design. 4. Balanced Incomplete Block Designs. 5. Correlation Effects. 6. Categorical Data for Randomized Block Designs. 7. Goodness of Fit. 8. Concluding Remarks. References. Subject Index. Author Index. Examples Index

Nonparametrics for Sensory Science: A More Informative Approach

A procedure for grouping food consumption data for use in food allergen risk assessment

We show that adding replications in replicated difference tests results in larger power and smaller variance when the number of assessors is fixed. On the other hand, when the number of total assessments is fixed, the power usually decreases and the variability increases whenever replications are considered instead of different assessors. The appropriate numbers of assessor needed to gain the same power and variability, respectively, when replications are used will be given. It is shown that the number of assessors might indeed be reduced, but this has to be paid for by an increasing total number of assessments. We show that two key models, namely the mixture binomial and a corrected version of the Beta-binomial model, are quite similar with respect to the properties of interest. We provide tables from tvhich, according to her/his requirements, the investigator might find an appropriate setting with respect to the number of assessors and replications.

The design of replicated difference tests

A comparison of methods for linear prediction of apple flavour from gas chromatographic measurements

/pdf/the-design-of-replicated-difference-tests-76yxds2ehn.pdf

Per B. Brockhoff

Papers

Nonparametrics for Sensory Science: A More Informative Approach

A procedure for grouping food consumption data for use in food allergen risk assessment

The design of replicated difference tests

A comparison of methods for linear prediction of apple flavour from gas chromatographic measurements

The Design of Replicated Difference Tests