An R and S-Plus Companion to Applied Regression by John Fox

By John Fox

"This publication matches into a wanted area of interest: rigorous adequate to provide complete clarification of the facility of the S language, but available adequate to assign to social technological know-how graduate scholars with no worry of intimidation. it's a great stability of utilized statistical "firepower" and considerate rationalization. It meets the entire very important mechanical wishes: every one instance is given intimately, code and information are freely on hand, and the nuances of types are given instead of simply the naked necessities. It additionally meets a few very important theoretical wishes: linear versions, specific information research, an creation to using GLMs, a dialogue of version diagnostics, and precious directions on writing personalized capabilities. "

-Jeff Gill, college of Florida, Gainesville

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Each group is administered only one of two test forms. Thus, the resulting data are two independent variables xi (i D 1; : : : ; nx ) and yj (j D 1; : : : ; ny ). When tests are given to groups at different time points, and the composition of test takers in the groups have changed over time, it has been shown that adopting an EG design is sometimes problematic because the assumption of equivalence might not hold (Lyrén and Hambleton 2011). 3 Counterbalanced Design Similar to the EG design, in the counterbalanced (CB) design two independent groups of test takers are sampled from the same population T.

The test contains 40 multiple-choice items scored incorrect (0) or correct (1). Test form X was administered to 4,329 examinees and test form Y to 4,152 examinees. 5 of Kolen and Brennan (2014) as score frequencies. We will refer to these data as the ACT data set. Both the equate and SNSequate packages include the ACT data set as the objects ACTmath and ACTmKB, respectively. Both objects contain the score scale, score frequencies for test form X, and the score frequencies for test form Y. © Springer International Publishing AG 2017 J.

The assumed equating design is set using the argument design with default values design = "eg" (EG design) and design = "ng" (NEAT design) for univariate and multivariate score distributions, respectively. The SG and CB designs are specified using the options "sg" and "cb", respectively. The kequate package has the kefreq() function whose functionality is very similar to that of freqtab() in equate. A typical call to kefreq() reads as kefreq(in1, xscores, in2, ascores) where in1 and in2 are vectors containing scores on test form X and on test forms Y or A (the anchor test), respectively.

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