Measurement Development and Evaluation

Literature Cited

1. Brown A, Maydeu-Olivares A. 2013. How IRT can solve problems of ipsative data in forced-choice questionnaires. Psychol. Methods 18:136–52
   [Google Scholar]
2. Buckles S, Walstad WB. 2008. The national assessment of educational progress in economics: test framework, content specifications, and results. J. Econ. Educ. 39:1100–6
   [Google Scholar]
3. Cao M, Drasgow F, Cho S 2015. Developing ideal intermediate personality items for the ideal point model. Organ. Res. Methods 18:2252–75
   [Google Scholar]
4. Chang EC, Maydeu-Olivares A, D'Zurilla TJ 1997. Optimism and pessimism as partially independent constructs: relationship to positive and negative affectivity and psychological well-being. Personal. Individ. Differ. 23:3433–40
   [Google Scholar]
5. Clark LA, Watson D. 2019. Constructing validity: new developments in creating objective measuring instruments. Psychol. Assess. In press
   [Google Scholar]
6. Couper MP, Tourangeau R, Conrad FG, Singer E 2006. Evaluating the effectiveness of visual analog scales: a web experiment. Soc. Sci. Comput. Rev. 24:2227–45
   [Google Scholar]
7. Crawford JR, Henry JD. 2004. The Positive and Negative Affect Schedule (PANAS): construct validity, measurement properties and normative data in a large non‐clinical sample. Br. J. Clin. Psychol. 43:3245–65
   [Google Scholar]
8. Dalal DK, Carter NT, Lake CJ 2014. Middle response scale options are inappropriate for ideal point scales. J. Bus. Psychol. 29:3463–78
   [Google Scholar]
9. DeVellis RF. 2003. Scale Development: Theory and Applications Thousand Oaks, CA: SAGE. , 2nd ed..
10. Diamantopoulos A, Siguaw JA. 2006. Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. Br. J. Manag. 17:4263–82
    [Google Scholar]
11. Drasgow F, Chernyshenko OS, Stark S 2010. 75 years after Likert: Thurstone was right!. Ind. Organ. Psychol. 3:4465–76
    [Google Scholar]
12. Dwight SA, Donovan JJ. 2003. Do warnings not to fake reduce faking. ? Hum. Perform. 16:11–23
    [Google Scholar]
13. Ellis BB, Mead AD. 2002. Item analysis: theory and practice using classical and modern test theory. Blackwell Handbooks of Research Methods in Psychology: Handbook of Research Methods in Industrial and Organizational Psychology SG Rogelberg 324–43 Malden, MA: Blackwell Publ.
    [Google Scholar]
14. Embretson SE, Reise SP. 2000. Item Response Theory for Psychologists Mahwah, NJ: Lawrence Erlbaum
15. Fabrigar LR, Wegener DT, MacCallum RC, Strahan EJ 1999. Evaluating the use of exploratory factor analysis in psychological research. Psychol. Methods 4:3272–99
    [Google Scholar]
16. Fives H, DiDonato-Barnes N. 2013. Classroom test construction: the power of a table of specifications. Pract. Assess. Res. Eval. 18:31–7
    [Google Scholar]
17. Gierl MJ, Haladyna TM, eds. 2013. Automatic Item Generation: Theory and Practice New York: Routledge
18. Gorsuch RL. 1983. Factor Analysis Hillsdale, NJ: Lawrence Erlbaum Assoc.
19. Gynther MD, Burkhart BR, Hovanitz C 1979. Do face-valid items have more predictive validity than subtle items? The case of the MMPI Pd scale. J. Consult. Clin. Psychol. 47:2295–300
    [Google Scholar]
20. Haladyna TM, Rodriguez MC. 2013. Developing and Validating Test Items New York: Routledge
21. Hayton JC, Allen DG, Scarpello V 2004. Factor retention decisions in exploratory factor analysis: a tutorial on parallel analysis. Organ. Res. Methods 7:2191–205
    [Google Scholar]
22. Hernández A, Drasgow F, González-Romá V 2004. Investigating the functioning of a middle category by means of a mixed-measurement model. J. Appl. Psychol. 89:4687–99
    [Google Scholar]
23. Highhouse S, Nye CD, Zhang DC 2019. Dark motives and elective use of brainteaser interview questions. Appl. Psychol. 68:2311–40
    [Google Scholar]
24. Hollrah JL, Schlottmann RS, Scott AB, Brunetti DG 1995. Validity of the MMPI subtle items. J. Personal. Assess. 65:2278–99
    [Google Scholar]
25. Jackson DL, Gillaspy JA Jr, Purc-Stephenson R 2009. Reporting practices in confirmatory factor analysis: an overview and some recommendations. Psychol. Methods 14:16–23
    [Google Scholar]
26. Landers RN, Sackett PR, Tuzinski KA 2011. Retesting after initial failure, coaching rumors, and warnings against faking in online personality measures for selection. J. Appl. Psychol. 96:1202–10
    [Google Scholar]
27. MacCallum RC, Widaman KF, Zhang S, Hong S 1999. Sample size in factor analysis. Psychol. Methods 4:184–99
    [Google Scholar]
28. Malamut A, Van Rooy DL, Davis VA 2011. Bridging the digital divide across a global business: development of a technology‐enabled selection system for low‐literacy applicants. Technology‐Enhanced Assessment of Talent NT Tippins, S Adler 267–92 San Francisco, CA: Jossey Bass
    [Google Scholar]
29. McCloy RA, Heggestad ED, Reeve CL 2005. A silk purse from the sow's ear: retrieving normative information from multidimensional forced-choice items. Organ. Res. Methods 8:2222–48
    [Google Scholar]
30. Min H, Zickar M, Yankov G 2018. Understanding item parameters in personality scales: an explanatory item response modeling approach. Personal. Individ. Differ. 128:1–6
    [Google Scholar]
31. Nunnally JC. 1978. Psychometric Theory Hillsdale, NJ: McGraw-Hill. , 2nd ed..
32. Nye CD, Drasgow F. 2011. Assessing goodness of fit: Simple rules of thumb simply do not work. Organ. Res. Methods 14:3548–70
    [Google Scholar]
33. Olson-Buchanan JB, Drasgow F, Moberg PJ, Mead AD, Keenan PA, Donovan MA 1998. Interactive video assessment of conflict resolution skills. Pers. Psychol. 51:11–24
    [Google Scholar]
34. Park G, Schwartz HA, Eichstaedt JC, Kern ML, Kosinski M et al. 2015. Automatic personality assessment through social media language. J. Personal. Soc. Psychol. 108:6934–52
    [Google Scholar]
35. Russell SS, Spitzmüller C, Lin LF, Stanton JM, Smith PC, Ironson GH 2004. Shorter can also be better: the abridged job in general scale. Educ. Psychol. Meas. 64:5878–93
    [Google Scholar]
36. Schriesheim CA, Eisenbach RJ. 1995. An exploratory and confirmatory factor-analytic investigation of item wording effects on the obtained factor structures of survey questionnaire measures. J. Manag. 21:61177–93
    [Google Scholar]
37. Schwarz N. 1999. Self-reports: how the questions shape the answers. Am. Psychol. 54:293–105
    [Google Scholar]
38. Shaffer JA, DeGeest D, Li A 2016. Tackling the problem of construct proliferation: a guide to assessing the discriminant validity of conceptually related constructs. Organ. Res. Methods 19:180–110
    [Google Scholar]
39. Sliter KA, Zickar MJ. 2014. An IRT examination of the psychometric functioning of negatively worded personality items. Educ. Psychol. Meas. 74:2214–26
    [Google Scholar]
40. Spector PE, Rogelberg SG, Ryan AM, Schmitt N, Zedeck S 2014. Moving the pendulum back to the middle: reflections on and introduction to the inductive research special issue of Journal of Business and Psychology. J. Bus. Psychol. 29:4499–502
    [Google Scholar]
41. Stark S, Chernyshenko OS, Drasgow F, White LA 2012. Adaptive testing with multidimensional pairwise preference items: improving the efficiency of personality and other noncognitive assessments. Organ. Res. Methods 15:3463–87
    [Google Scholar]
42. Swain SD, Weathers D, Niedrich RW 2008. Assessing three sources of misresponse to reversed Likert items. J. Mark. Res. 45:1116–31
    [Google Scholar]
43. Thurstone LL. 1927. A law of comparative judgment. Psychol. Rev. 34:4273–86
    [Google Scholar]
44. Vergauwe J, Wille B, Hofmans J, Kaiser RB, Fruyt FD 2017. The too little/too much scale: a new rating format for detecting curvilinear effects. Organ. Res. Methods 20:3518–44
    [Google Scholar]
45. von Davier M, Carstensen CH 2007. Multivariate and Mixture Distribution Rasch Models: Extensions and Applications New York: Springer
46. Wainer H, Dorans NJ, Flaugher R, Green BF, Mislevy RJ 2000. Computerized Adaptive Testing: A Primer New York: Routledge
47. Weijters B, Baumgartner H. 2012. Misresponse to reversed and negated items in surveys: a review. J. Mark. Res. 49:5737–47
    [Google Scholar]
48. Weijters B, Baumgartner H, Schillewaert N 2013. Reversed item bias: an integrative model. Psychol. Methods 18:320–34
    [Google Scholar]
49. Winkielman P, Knäuper B, Schwarz N 1998. Looking back at anger: Reference periods change the interpretation of emotion frequency questions. J. Personal. Soc. Psychol. 75:3719–28
    [Google Scholar]
50. Zhang Y, Waldman DA, Han YL, Li XB 2015. Paradoxical leader behaviors in people management: antecedents and consequences. Acad. Manag. J. 58:2538–66
    [Google Scholar]
51. Zickar MJ. 2012. A review of recent advances in item response theory. Research in Personnel and Human Resources Management JJ Martocchio, A Joshi, H Liao 145–76 Bingley, UK: Emerald Group Publ.
    [Google Scholar]
52. Zickar MJ, Gibby RE. 2006. A history of faking and socially desirable responding on personality tests. A Closer Examination of Applicant Faking Behavior RE Griffith, MH Peterson 21–42 Charlotte, NC: Information Age Publ.
    [Google Scholar]
53. Zickar MJ, Gibby RE, Robie C 2004. Uncovering faking samples in applicant, incumbent, and experimental data sets: an application of mixed-model item response theory. Organ. Res. Methods 7:2168–90
    [Google Scholar]
54. Zickar MJ, Ury KL. 2002. Developing an interpretation of item parameters for personality items: content correlates of parameter estimates. Educ. Psychol. Meas. 62:119–31
    [Google Scholar]