Monitoring Metabolic Status Predicting Decrements in Physiological and Cognitive Performance (2004) / Chapter Skim
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2 The Study of Individual Differences: Statistical Approaches to Inter- and Intraindividual Variability
2 The Study of Individual Differences: Statistical Approaches to Inter- and Intraindividual Variability
Pages 37-52
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From page 37... ...
The typical research design oversimplifies the complexity of these relationships and thus does not unambiguously allow for inferences about organism-environment interactions. Rather, these designs tend to obscure underlying processes by shrouding rich individual data with group data aggregation procedures (Glass and Mackey, 1988; O'Connor, 1990~.
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From page 38... ...
Furthermore, precise mapping of physiological activity from these distinct periods onto experimental manipulations is fraught with hazards, such as delayed physiological responses and compensatory homeostatic processes (Levenson, 1988~. Alternatively, all recorded activity might be considered as relevant; functional relationships among ongoing physiological processes could then be extracted across observations (O'Connor, 1990~.
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From page 39... ...
RESEARCH: WHAT ARE WE REALLY TRYING TO DO? Variance Partitioning and Hypothesis Testing The research enterprise is primarily concerned with the detection of systematic relationships amidst the morass of variability in biobehavioral responses.
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From page 40... ...
The Alpha Level or Type I Error Rate The Type I error rate is the probability of falsely rejecting the null hypothesis, that is, the chance of concluding that a systematic relationship exists in the population when in fact it does not. This possibility tends to dominate the consciousness of investigators, so many post-hoc techniques (e.g., the Bonferoni inequality, the Newman-Keuls test)
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From page 41... ...
The following equation reveals the relationship between the statistical test value on the one hand, and the effect size and size of the study on the other: Statistical (i.e., significance) test = effect size x size of the study or more concretely for a two-group test: F = mean square error of interest - mean square error of noninterest x dfdenorninator with the appropriate F distribution based on the numerator and denominator dips and the mean squares representing the variability per df: Thus the numerator is an estimate of the variability of interest and the denominator is an estimate of the variability of noninterest (Rosenthal and Rosnow, 19844.
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From page 42... ...
That this choice often occurs without full knowledge of the various selection effects threatens not only the validity of the inferences drawn from such experiments, but also ultimately the quality of research that serves as the collective database of the field. Nesselroade and Jones (1991)
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From page 43... ...
Yet there has generally been a paucity of multivariate studies in experimental psychology and in experimental research in general (Harris, 1992~. In addition, the occasions dimension holds particular significance for biobehavioral research since most studies involve repeated measurements to some degree (Vasey and Thayer, 1987~.
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From page 44... ...
Furthermore, a significant p value found in any one study yields essentially no useful information regarding the probability of replicating that finding (Goodman, 1992; Guttman, 1985~. Inter- Versus Intraindividual Variability An important and often overlooked distinction that has led to confusion in the literature is the difference between inter- and intraindividual variability.
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From page 45... ...
In a related study, it was reported that the physiological measures that best discriminated the group emotion profiles were not those that best discriminated among any individual's emotion profiles (Thayer and Faith, 19944. These findings suggest that the effects of confounding inter- and intraindividual variability can have enormous consequences for the generalizations and conclusions reached in any particular study.
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From page 46... ...
An Example Using Multilevel Models Recent advances in statistical software have brought the use of hierarchical linear models and stochastic regression models into easy reach. PROC MIXED in the SAS software package (SAS Institute Inc.)
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From page 47... ...
found that the average intraindividual effect of being at work versus at home on systolic blood pressure was 2 to 4 mm Hg. Thus the implications of this result are easy to comprehend, whereas traditional ANOVA-type models may state results in standard deviation units or other derived indices, the practical significance of which is often difficult to gauge.
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From page 48... ...
Timeseries analysis has been used extensively in many fields, from econometrics to physiology, and it allows for He examination of the temporal structure of a set of sequentially collected data points. Time series from individual subjects can be examined and parameters extracted that can be used in data aggregation procedures.
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From page 49... ...
1966. Multivariate behavioral research and the integrative challenge.
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1999. Ambulatory blood pressure responses and the circumplex model of mood: A 4-day study.
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From page 51... ...
1997. Physical Training Interventions to Reduce Stress Fracture Incidence in Navy and Marine Corps Recruit Training.
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From page 52... ...
Integr Physiol Behav Sci 30:4~67. Tyrrell RA, Pearson MA, Thayer JF.
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