The dissertation presents evidence on the measurement properties of self-report items in contemporary organizational contexts (Podsakoff & Organ, 1986). Operationally, the dissertation adopts a construct representation approach to construct validity, defined by the response processes engaged for measurement performance in trait assessment (AERA, 2014; Embretson, 1983). For example, self-report measures are known to be affected by a variety of variables, such as semantic and referent features (Cermac & Craik, 1979; Kelly, 1955) and design factors that impact cognitive context (Stone, et al, 2000; The Science of Self-Report). In turn, the response processes impacts the external correlations (Embretson, 2007). To the extent that semantic-referent features and design factors are construct-irrelevant, reduced external correlations can be expected. This dissertation presents evidence from a qualitative review of self-report future time perspective (FTP) instruments across organizational and retirement contexts. A quantitative review compares external correlates of the two instruments. A retrospective-observational study benchmarks the psychometric properties of Carstensen's self-report instrument using modern latent-variable modeling (item-response theory [IRT]). Structural equation modeling (SEM) is further used to test for moderating effects of subjective life expectancy (SLE) on latent predictors of FTP and retirement plans. Evidence from a '3 x 2' mixed-subjects experimental design is also presented indicating the effects of subjective life expectancy (SLE) on measurement error in personality factors, FTP, and retirement plans. Discussion centers on advancing measurement paradigms in psychological and education research, as well as -more generally- adopting an integrated perspective of construct validity for advancing and evaluating substantive research.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54841 |
| Date | 27 May 2016 |
| Creators | Kerry, Matthew James |
| Contributors | Embretson, Susan E. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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