April 20, 2017

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By Engler D. A.

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Extra info for A pseudolikelihood approach for simultaneous analysis of array comparative genomic hybridizations (2

Sample text

Such is not the case with regard to internal validity. There is greater potential for low internal validity with nonmanipulable grouping variables than with manipulable ones, where random assignment of units to a level of the grouping variable is possible. In group comparison problems involving nonmanipulable grouping variables, internal validity is of particular concern. If group differences result, we would like to attribute these differences to the grouping variable and not to some intervening variable(s).

The basic concern in sampling is that of representativeness of some meaningful population (defined in terms of analysis units). The degree of representativeness is assessed in great part by researcher judgment; a description and documentation of the sampled units should help. Random sampling is championed by some methodologists, but it is difficult to implement and sometimes not entirely appropriate in practice. Simple random selection does not necessarily ensure representativeness. That is, by chance a “random” sample could be atypical of the target population.

To introduce the matrix operations we will begin with a research context and a small data set. Using these data we will demonstrate how the data may be manipulated, analyzed, and summarized. The matrix operations we present in this chapter will be used throughout the book to examine group separation and classification. 2 RESEARCH CONTEXT We begin with the context for a research study by Baumann, Seifert-Kessell, and Jones (1992). ”) The researchers were interested in comparing three strategies for teaching reading comprehension to fourth-grade students (our “analysis units”).

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