By Holmes Finch
The ebook may be designed essentially for graduate scholars (or complicated undergraduates) who're studying psychometrics, in addition to execs within the box who want a reference to be used of their perform. we might imagine that clients have a few simple wisdom of utilizing SAS to learn information and behavior simple analyses (e.g., descriptive information, frequency distributions). furthermore, the reader could be conversant in simple statistical innovations comparable to descriptive records (e.g., suggest, median, variance, commonplace deviation), percentiles and the rudiments of speculation checking out. they need to actually have a passing familiarity with concerns in psychometrics comparable to reliability, validity and test/survey scoring. we won't suppose any longer than uncomplicated familiarity with those matters, and should commit a element of every one bankruptcy (as good because the complete first bankruptcy) to reviewing a lot of those easy principles for these no longer accustomed to them. We envision the e-book as being important both as a prime textual content for a path on utilized dimension the place SAS is the most platform for guide, or as a complement to a extra theoretical textual content. We additionally expect that readers operating in govt enterprises chargeable for checking out and size concerns on the neighborhood, kingdom and nationwide degrees, and personal checking out, survey and marketplace study businesses, in addition to college contributors desiring a realistic source for psychometric perform will function a marketplace for the booklet. in brief, the readership would come with graduate scholars, college participants, information analysts and psychometricians answerable for research of survey reaction information, in addition to academic and mental tests. The aim of the publication is to supply readers with the instruments helpful for assessing the psychometric features of academic and mental measures in addition to surveys and questionnaires. each one bankruptcy will conceal a topic pertinent to psychometric and dimension perform, with an emphasis on software. themes might be in short mentioned from a theoretical/technical point of view so that it will give you the reader with the history essential to properly use and interpret the statistical analyses that might be offered accordingly. Readers will then be provided with examples illustrating a specific proposal (e.g., reliability). those examples will contain a dialogue of the actual research, in addition to the SAS code essential to behavior them. The ensuing output will then be mentioned intimately, targeting the translation of the implications. ultimately, examples of the way those effects could be written up can also be incorporated within the textual content. it's was hoping that this mix of thought with examples of tangible perform will serve the reader either as a pedagogical software and as a reference paintings.
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Additional resources for Applied Psychometrics using SAS
This last issue would be particularly important for longer times assessments where fatigue and speediness may have very real impacts on test performance. In the following example with SAS, we will use the 20 dichotomous item measure discussed above, splitting the items into odd and even halves. With this program, our goal is to first create scores for the odd and even items, calculate the correlation between scores using proc corr, and read the resulting correlation into a new dataset where we can insert it into the Spearman-Brown equation.
These two halves are then scored individually, and the correlation between the scores is calculated. This correlation can be viewed as an estimate of the reliability of the two halves in that we assume they represent parallel forms of the same measure. However, this correlation reflects the reliability estimate for an instrument that is half as long as the actual one to be used, because we have split it in half. Therefore, we need to make a correction to this value to reflect reliability for the full instrument with our sample.
In addition, they conducted a simulation study to compare the various methods in terms of their accuracy and found that across many conditions, they performed similarly, except for a very small sample of 10 examinees, in which case the ADF approach was somewhat less accurate. The macro for calculating these intervals appears below, followed by the resultant output. Of key Reliability 41 importance here is that the items be named X1, X2, and so on, which is how the macro code expects them to be named.