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One way to investigate different translations is to have one or more translators make a first translation to the target language and then have one or more independent translators make a translation back to the original language (Brislin, 1970). Comparison of the original source version with the back-translated version is a valuable procedure for checking linguistic accuracy. In most cases, this method can detect items that have been poorly translated from a linguistic point of view, and, ideally, the complete process should be repeated for these items. If the two versions are highly similar, the comparison suggests that the target version is equivalent to the source language form. However, it must be remembered that apparent equivalence may be created by factors that have nothing to do with the quality of the translation: Translators may have a shared set of rules for translating certain nonequivalent words and phrases, and some back translators may be able to make sense of a poor target language version.

Personal Globe Inventory Circumplex (PGI), 411, 413, 414, 415, 416, 418 Personality, measuring: approaches to construct validation, 379 380 constructs, 380 384 validity, 384 388 empirical, 377 378 rational-theoretical, 377 statistical, 378 379 overview, 403 test items evaluation of, 393 398 generation, 388 response properties, 390 393 stimulus properties, 388 390 validation and extension, 398 403 Personality Assessment Inventory (PAI), 381, 382, 386, 389, 393, 394, 397 Personality deviance, 382 Personality disorder, 194 Personality Research Form, 397 Person-characteristic curve (PCC), 436 437 Person-free item calibration, 438 Philosophy and Principles of Data Analysis, 34 Pigeons, studies involving, 275, 283 Place effects, 254 Plasmodes, 153, 158 Platykurtic, 117, 651 Polyserials, 431 Porphyria hepatica, 601 Positive Affect. See Mood measurement, Positive Affect Positive and Negative Affect Schedule (PANAS), 356 358, 360 Expanded Form (PANAS-X), 351, 361, 372 measurement error and, 364, 366 368, 369, 370, 371 Positron-emission tomography (PET): neuropsychology and, 289, 297 298, 306 applications, 308 309 fMRI and, 310 rationale, 307 308 rCBF and, 308 309 strengths/limitations, 309 Posttest-only nonequivalent-groups design, 331 332 Posttraumatic stress disorder (PTSD), 195, 199, 201 Power analysis: correlation, 82 84 factors in uencing, 67 71 heteroscedasticity and, 66, 72, 74, 79 80 lower power, 75 76 overview, 65 67, 84 probability coverage, 79 80, 81 rank-based methods, 78 regression, 78 82 robust estimators, 75 76, 78, 80 82 sample size and, 71 74, 78 skewness and, 66, 68, 72, 74 75 trimmed means, 76 78 Pragmatism, 39 Predictive density criterion (PDC), 587, 589 Predictive least absolute value (PLAV), 587, 589 Predictive minimum descriptive length (PMDL), 587, 589 Predictors, centering, 488 490 Pretest-posttest one-group design, 330

Finally, certain algorithms are centralized while others are distributed Centralized algorithms typically compute more exact positions and can be competitive in situations where accuracy is important and the ex ltration of ranging data and dissemination of resulting location data is not prohibitively time-consuming nor errorprone Centralized algorithms could actually be a viable option in many typical deployments where a base station is already needed for other reasons Distributed algorithms are often local approximations to centralized algorithms, but have the virtue that they do not depend on a large centralized computer and potentially have better scalability Other issues to consider are battery life and communication costs Often these two are intertwined, as typically communication is the most battery-draining.

It is beyond the scope of a book such as this to discuss genetics in any detail, and so I will assume that the majority of readers will have a basic grasp of the terminology and processes involved in the transmission of genetic material from generation to generation and of patterns of heredity If you do not it would not be a waste of your time were you to read an introductory textbook on the subject In the context of this chapter I think that it is enough to remind ourselves that chromosomes consist of a double helix of DNA and that speci c sections of this DNA act as templates for the production of proteins.

Setting (New channel) Sort Mode Video Source Hide channels without channel number Channel Scanner Transport Editor Default No default value assigned Channel Name (All) Unchecked Description Create a new Channel Settings. Default Sort Mode: either Channel Name or Channel Number Default Video Source(s) from which to obtain channel information If set, the channels missing a number do appear in the EPG. Scan for channel lineup. Simplifies ATSC setup so you don t have to edit the database directly

These sections of DNA are termed genes and their speci c sites on the chromosome are termed loci (not all proteins are the product of a single gene but we really do not need to worry about that in this context) Each individual gene is always at the same locus and it always codes for the same protein This means that it also always affects the same character in the organism, be that an aspect of behavior, physiology, or growth form There is however an element of variation possible within individual genes that translates into variation in the phenotypes affected by them For example, in humans the gene for eye color exists as a number of variants each of which results in a different eye color The different forms of the gene are termed alleles.