2 resultados para multiple data

em Bucknell University Digital Commons - Pensilvania - USA


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Researchers examining the effects of programs, in this case a state-level pharmaceutical assistance program for the elderly, sometimes must rely on multiple methods of data collection. Two-stage data collection (e.g., a telephone interview followed by a mail questionnaire) was used to obtain a full range of information. Older age groups were found to participate less frequently in the telephone interview, while certain demographic factors characterized mail questionnaire nonparticipants, all of which supports past research. Results also show that those in the poorest health are less likely to participate in the mail survey. Combining the two methods did not result in high attrition, suggesting that innovation can be successfully employed. Knowledge of the bias associated with each method will aid in targeting special groups.

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The Multiple Affect Adjective Check List (MAACL) has been found to have five first-order factors representing Anxiety, Depression, Hostility, Positive Affect, and Sensation Seeking and two second-order factors representing Positive Affect and Sensation Seeking (PASS) and Dysphoria. The present study examines whether these first- and second-order conceptions of affect (based on R-technique factor analysis) can also account for patterns of intraindividual variability in affect (based on P-technique factor analysis) in eight elderly women. Although the hypothesized five-factor model of affect was not testable in all of the present P-technique datasets, the results were consistent with this interindividual model of affect. Moreover, evidence of second-order (PASS and Dysphoria) and third-order (generalized distress) factors was found in one data set. Sufficient convergence in findings between the present P-technique research and prior R-technique research suggests that the MAACL is robust in describing both inter- and intraindividual components of affect in elderly women.