Impression management, candor, and microcomputer-based organizational surveys: An individual differences approach

Rosenfeld, Paul; Giacalone, Robert A.; Knouse, Stephen B.; Doherty, Linda M.; Vicino, S. Mitchell; Kantor, John; Greaves, Jean

doi:10.1016/0747-5632(91)90026-w

Cited by 34 publications

(16 citation statements)

References 35 publications

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“…Previous research has indicated that responses to computer based attitude assessments can vary depending upon respondents' beliefs about anonymity (e.g., Kantor, 1991). Likewise, Rosenfield, Giacolone, Knouse, and Doherty (1991) found an interaction between an individual difference variable (self-monitoring) and administration medium (computer vs. paper and pencil). King and Miles (1995) results matched this finding.…”

Section: Discussionmentioning

confidence: 81%

An Empirical Assessment of Data Collection Using the Internet

Stanton

1998

Personnel Psychology

387

279

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Identical questionnaire items were used to gather data from 2 samples of employees. One sample (n= 50) responded to a survey implemented on the World Wide Web. Another sample (n= 181) filled out a paper version of the survey. Analyses of the 2 data sets supported an exploration of the viability of World Wide Web data collection. The World Wide Web data had fewer missing values than the paper and pencil data. A covariance analysis simultaneously conducted in both samples indicated similar covariance structures among the tested variables. The costs and benefits of using access controls to improve sampling are discussed. Four applications that do not require such access controls are discussed.

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Section: Discussionmentioning

confidence: 81%

An Empirical Assessment of Data Collection Using the Internet

Stanton

1998

Personnel Psychology

387

279

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“…We need to be sure that particular kinds of responses are not systematically excluded; for this purpose convenience samples are less satisfactory than other methods 33 . Finally, some research 34,35 has suggested that those who respond to computer-administered surveys differ systematically in the way they answer questions from those who respond to paper surveys. But selection bias is not inevitable.…”

Section: Epinetmentioning

confidence: 99%

Health surveys via the Internet: Quick and dirty or rapid and robust?

et al. 2000

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“…Applying traditional correlation or regression analyses to data obtained via RR is inappropriate, however, as the randomization component of the RR distorts the response variable. A simple approach to circumvent this problem is to perform a median-split on a continuous covariate and to compare the estimates across the resulting groups (e.g., Latkin and Vlahov 1998;Ostapczuk and Musch 2011;Rosenfeld et al 1991;Soeken and Macready 1986;Hilbig, Moshagen, and Zettler 2015). However, median-splits suffer from several shortcomings, including loss of information, decreased power, and difficulties when considering more than one variable at a time (Royston, Altman, and Sauerbrei 2006).…”

Section: Introductionmentioning

confidence: 99%

RRreg: An R Package for Correlation and Regression Analyses of Randomized Response Data

Heck¹,

Moshagen²

2018

J. Stat. Soft.

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The randomized response (RR) technique was developed to improve the validity of measures assessing attitudes, behaviors, and attributes threatened by social desirability bias. The RR removes any direct link between individual responses and the sensitive attribute to maximize the anonymity of respondents and, in turn, to elicit more honest responding. Since multivariate analyses are no longer feasible using standard methods, we present the R package RRreg that allows for multivariate analyses of RR data in a user-friendly way. We show how to compute bivariate correlations, how to predict an RR variable in an adapted logistic regression framework (with or without random effects), and how to use RR predictors in a modified linear regression. In addition, the package allows for power analysis and robustness simulations. To facilitate the application of these methods, we illustrate the benefits of multivariate methods for RR variables using an empirical example.

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Impression management, candor, and microcomputer-based organizational surveys: An individual differences approach

Cited by 34 publications

References 35 publications

An Empirical Assessment of Data Collection Using the Internet

An Empirical Assessment of Data Collection Using the Internet

Health surveys via the Internet: Quick and dirty or rapid and robust?

RRreg: An R Package for Correlation and Regression Analyses of Randomized Response Data

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