How to conduct a standalone systematic literature review

How to conduct a standalone systematic literature review: a guide for social science scholars 

Rasch Measurement Theory

Educational and psychological measurement in the first half of the twentieth century was dominated by what I have called the Test Score Tradition (Engelhard, 2013). As its label suggests, the Test Score Tradition is dominated by sum scores with Classical Test Theory as a key example of measurement research in this tradition (Crocker and Algina, 1986). The second half of the 20th century witnessed the emergence of a Scaling Tradition that recognized the duality between items and person scores (Mosier, 1940, 1941).

As pointed out by van der Linden (2016), Rasch was one of the pioneers within the tradition that represented a paradigm shift from earlier measurement research. Rasch (1960), presented a set of ideas and methods described by Loevinger (1965) as a “truly new approach to psychometric problems” (p. 151) that can lead to “nonarbitrary measures” (p. 151). Rasch sought to develop “individual-centered statistical techniques [that] require models in which each individual is characterized separately and from which, given adequate data, the individual parameters can be estimated” (Rasch, 1960, p. xx).

Problems of invariant measurement played a central role in the development of Rasch’s measurement theory. As pointed out by Andrich (1988), Rasch presented “two principles of invariance for making comparisons that in an important sense precede though inevitably lead to measurement” (p. 18). Problems related to invariance played a key role in motivating his measurement theory. Rasch’s concept of specific objectivity and his principles of comparison form his version of the requirements for invariant measurement (Rasch, 1977). In his words,

 The comparison between two stimuli should be independent of which particular individuals were instrumental for the comparison; and it should also be independent of which stimuli within the considered class were or might also have been compared . Symmetrically, a comparison between two individuals should be independent of which particular stimuli within the class considered were instrumental for the comparison; and it should be independent of which other individuals were also compared, on the same or on some other occasion (Rasch, 1961, pp. 331–332).

 It is clear in this quotation that Rasch recognized the importance of both personinvariant item calibration, and item-invariant measurement of persons. In fact, he made them cornerstones in his quest for specific objectivity. In order to address problems related to invariance, Rasch laid the foundation for the development of a family of measurement models that are characterized by the potential to separate item and person parameters (Wright & Masters, 1982).

Andrich (1985) has made a strong and persuasive case for viewing the Rasch model as a probabilistic realization of a Guttman scale. Rasch measurement theory can be used to model the probability of dichotomous item responses as a logistic function of item difficulty and person location on the latent variable.

Figure above shows four item response functions based on the Rasch model. Model-data fit can then be based on the comparison between the observed and expected response patterns that is conceptually equivalent to other methods of evaluating a Guttman scale. Engelhard (2013) provides a description of several modeldata fit indices that can be used with the Rasch model. Rasch measurement theory (Rasch, 1960) provides a framework for meeting these requirements when acceptable model-data fit is obtained. Bond & Fox (2015) provide an accessible introduction to Rasch measurement theory.

Source: Wilson and Fisher (2017)

EXPLORATORY VERSUS CONFIRMATORY FACTOR ANALYSIS

There are two basic types of factor analysis: exploratory and confirmatory. Exploratory factor analysis (EFA) is used when the researcher does not know how many factors are necessary to explain the interrelationships among a set of characteristics, indicators, or items (Gorsuch, 1983; Pedhazur & Schmelkin, 1991; Tabachnick & Fidell, 2001). Therefore, the researcher uses the techniques of factor analysis to explore the underlying dimensions of the construct of interest. This was the approach that Leske (1991) used in her conceptualization of the dimensions of needs of families of the critically ill. EFA is the most commonly used form of factor analysis in health care research. It is what we will use to examine the dimensions of Concerns About Genetic Testing.

In contrast, confirmatory factor analysis (CFA) is used to assess the extent to which the hypothesized organization of a set of identified factors fits the data (Nunnally & Bernstein, 1994; Pedhazur & Schmelkin, 1991). It is used when the researcher has some knowledge about the underlying structure of the construct under investigation. CFA could also be used to test the utility of the underlying dimensions of a construct identified through EFA, to compare factor structures across studies, and to test hypotheses concerning the linear structural relationships among a set of factors associated with a specific theory or model. Pett, Wampold, Turner, and Vaughan-Cole (1999), for example, used CFA to test a hypothesized model predicting the paths of influence of divorce on young children’s psychosocial adjustment.

When undertaking a factor analysis using EFA, it is common practice to use more traditional statistical computer packages (e.g., SPSS, SAS, and BMDP) for the statistical analyses. CFA, on the other hand, requires a comprehensive analysis of covariance structures (Byrne, 1989). This form of measurement model is available in structural equation modeling (SEM). LISREL (Jöreskog & Sörbom, 1989) and EQS (Bentler, 1985) are two statistical computer packages that are used to undertake SEM analyses.

Pet et al. (2003)

Author and Career success

No	Authors	Methodology:
1)	Hay, A and Hodgkinson, M. (2006)., Exploring MBA career success. Career Development International, 11, 2, 108-124	·         A total of 36 in-depth interviews were undertaken with MBA alumni which sought to capture the individual's own account of their career success in relation to their MBA. ·         The study utilised an inductive data analysis approach. ·         study conducted at top 15 business schools in the UK ·         interpretive approach ·         qualitative methods ·         purposive sampling ·         semi-structured interviews ·         inductive approach to data analysis (grounded theory)
2)	De Vos, A., De Hauw, S., and Van der Heijden, B. (2011). Competency development and career success: The mediating role of employability. Journal of Vocational Behavior, 79, 438–447	·         on-line survey, in a large financial institution located in Belgium, which employed about 16,000 white-collar workers at the time of our study ·         Simple random sampling, a total of 1050 employees to participate in an on-line survey. ·         final sample comprised 561 employees ·         five-point Likert scale ·         exploratory factor analysis ·         Chi-square test
6)	Akrivos, C., Ladkin, A., and Reklitis, P. (2007). Hotel managers’ career strategies for success. International Journal of Contemporary Hospitality Management, 19(2), 107-119.	·         case study approach ·         sample of 65 Greek deluxe hotel’s general managers ·         postal questionnaire ·         sample represented
8)	Hennequin, E. (2007). What “career success” means to blue-collar workers. Career Development International 12(6), 565-581.	·         French blue-collar workers, 25 interviews ·         qualitative approach, ·         Semi-structured interviews
11)	Ballout, H. I. (2008). Work-family conflict and career success: the effects of domain-specific determinant. Journal of Management Development, 27(5), 437-466.	·         Qualitative research ·         Drawing on existing theoretical and empirical evidence the paper develops and presents a conceptual framework of the relationships between domain-specific variables, work-family conflict, and career success. ·         The paper also presents propositions based on the relationships suggested by the framework
12)	Winchester, H. Lorenzo, S., Browning, L., and Chesterman, C. (2006). Academic women's promotions in Australian universities. Employee Relations, 28(6), 505 – 522.	·         examined promotions policies and procedures of 34 of 38 Australian Universities ·         qualitative content Analysis ·         interviews 17 universities ·         interviews were undertaken by two of the co-authors of this paper (both female). ·         interviewees were predominantly senior University staff, both male and female ·         Content analysis of Australian university promotion policies
14)	Rippon, J.H. (2005). Re-defining careers in education. Career Development International, 10(4), 275-292	·         qualitative ·         method: interview ·         Twelve participants ·         theoretical sampling ·         Grounded theory
18)	Gainor, K. A. (2006). Twenty-Five Years of Self-Efficacy in Career Assessment and Practice. Journal of Career Assessment 14(1), 161-178.	·         experimental and quasi-experimental studies ·         program evaluations studies ·         analog studies ·         program descriptions ·         concerning self-efficacy in career assessment and practice published in refereed professional journals during the past 25 years. ·         reviewed the literature review sections ·         31 articles
20)	Gubbins, M.C., and Garavan, T. N. (2005). Studying HRD Practitioners: A Social Capital Model. Human Resource Development Review, 4(2), 189-218.	·         Concept paper ·         Theoretical development
21)	Ismail, M.,  Mohd Rasdi, R., and Abdul Wahat, N. W. (2005). High-flyer women academicians: factors contributing to success. Women in Management Review 20(2), 117-132.	·         career-history method ·         in-depth interviews, combined with personal documents ·         study sample consists of women professors ·         31 women professors ·         were interviewed ·         recorder-cum-transcriber was used ·         Constant comparative analysis of data (Glaser and Strauss, 1967)
22)	Coleman, M. (2010). Women-only (homophilous) networks supporting women leaders in education. Journal of Educational Administration, 48, 6, 769-781.	·         two case studies of networks A and B ·         Qualitative research: semi-structured interviews ·         Network A had 20 members ·         Network B had 50 members.
23)	Enache, M., Sallan, J.M., Simo, P., Fernandez, V. (2011). Career attitudes and subjective career success: tackling gender differences. Gender in Management: An International Journal, 26(3), 234 – 250.	·         web-based survey ·         434 Spanish graduate and post-graduate distance-learning students of the psychology, business administration, humanities, communication, and law degrees ·         167 surveys were submitted by the respondents ·         eight-item scale and six-item scale ·         Cognitive interviews ·         Cronbach’s a coefficient ·         reliability analysis ·         Correlation analyses
24)	Bozionelos, N., Bozionelos, G., Kostopoulos, K., Polychroniou, P. (2011). How providing mentoring relates to career success and organizational commitment: A study in the general managerial population. Career Development International 16(5), 446-468	·         two cohorts of first year executive Master’s in Business Administration (MBA) students in a Business School ·         Questionnaires were handed in the class ·         365 completed questionnaires, 194 were included in the analysis ·         Descriptive statistics ·         Subjective career success measured with seven items from Gattiker and Larwood (1986) in a five-point response format ·         Mentoring received assessed with seven items on a five-point response ·         Format ·         Mentoring provided measured with a scale that contained eight items on a five-point response format ·         principal components analysis ·         varimax rotation ·         Pearson correlation coefficients
25)	Tharmaseelan, N., Inkson, K., and Carr, S.C. (2010). Migration and career success: testing a time-sequenced model. Career Development International 15(3), 218-238.	·         participants were Sri Lankans ·         Eight hundred questionnaires were distributed, of which 210 of the 221 returned questionnaires were usable, all from Sri Lankans 25 years or over ·         five-item scale incorporating the major themes of success indicated by Hall (1996) ·         Reliability tests (Cronbach’s a) ·         Regression analysis ·         Correlation analysis ·         Wash scale ·         Post-hoc analysis
26)	Thanacoody, P.R., Bartram, T., Barker, M., and Jacobs, K., (2006). Career progression among female Academics: A comparative study of Australia and Mauritius. Women in Management Review 21(7), 536-553.	·         case-study approach ·         Thirty in-depth interviews from two universities ·         data consisted of open-ended questions ·         Half of the interviews were tape-recorded and notes were also taken during all of the Interviews ·         Comparative analysis of data (Glaser and Strauss, 1967)
27)	Heslin, P.A. (2003). Self- and Other-Referent Criteria of Career Success. Journal of Career Assessment, 11(3), 262–286.	·         Part-time MBA students (N = 71) at a leading Canadian business school ·         Likert-type scale ranging from 1 (not too successful) to 7 (very successful). ·         test-retest reliability ·         open ended Question for H1 ·         Hypotheses 2, 3a, and 4 were assessed with a slightly modified version of the widely used career satisfaction scale developed by Greenhaus et al. (1990) ·         convergent and discriminant validity
28)	Lent, R.W., and Brown, S.D. (1996). The career development quarterly, Social cognitive approach to career development: an overview, 44, 4, 310-321	·         Concept paper ·         SCCT adopts Bandura’s (1986) triadic reciprocal model of causality
29)	Yeo, R.K., and Li, J. (2011). Working out the quality of work life: A career development perspective with insights for human resource management. Human Resource Management International Digest 19(3), 39-45.	·         US study of data collected between 2007-2009 from 140 working people who had decided to improve their career prospects and, thereby, their quality of work life, through professional education ·         data analysis
30)	Mohd Rasdi, R., Ismail, M., Uli, J., Mohd Noah, S. (2009). Career Aspirations and Career Success Among Managers in the Malaysian Public Sector. Research Journal of International Studies, 9, 21-35.	·         large cross-sectional career success study conducted on managers of Malaysian public sector organizations ·         quantitative survey ·         seven-point Likert-like scale ·         Cronbach’s Alpha ·         open-ended questions
31)	Sullivan, S.E., Baruch, Y., and Schepmyer, H. (2010). The Why, What, and How of Reviewer Education: A Human Capital Approach. Journal of Management Education,34(3), 393–429.	·         Concept paper
32)	Stumpf, S.A. (2010). Stakeholder competency assessments as predictors of career success. Career Development International, 15, 5, 459-478	·         342 people participated, 330 sample, participating in a MBA degree program (94 percent) or a corporate executive development program ·         Factor analyses ·         five-point response scales (Likert scale) ·         Principal Component Analysis with Varimax Rotation and Kaiser Normalization ·         simple correlations of the eight competency dimensions for each rater group
33)	Ahmad Tipu, S.A., and Manzoor Arain, F. (2011). Managing success factors in entrepreneurial ventures: a behavioral approach, International Journal of Entrepreneurial Behaviour & Research, 17(5), 534-560.	·         case-study approach ·         Three ventures from Pakistan’s food industry were selected ·         interviews ·         comparative analyses ·         semi-structured questionnaire ·         Thematic analysis of interview transcripts
35)	Ng, T.W.H., Eby, L.T., Sorensen, K.L., Feldman, D.C. (2005). Predictors of objective and subjective career success: A meta-analysis, Personnel Psychology, 58, 367-408.	·         Meta-analysis, ·         140 relevant articles. ·         Random sample of 30 studies. ·         correlation coefficient analysis. ·         average correlation ·         moderator analyses, used 15 studies and Q statistic ·         weighted least-squares multiple regression
36)	Mayrhofer, W., Meyer, M., Schiffinger, M., and Schmidt, A. (2008). The influence of family responsibilities, career fields and gender on career success: An empirical study. Journal of Managerial Psychology, 23(3), 292-323.	·         Questionnaire during the 2004 and 2005 follow-up surveys of a panel study started in 2000. The sample consists of 305 business school graduates ·         partial least squares (PLS) procedure ·         significance of the path coefficients was determined using a bootstrap procedure (e.g. Chin, 1998) with 500 subsamples ·         instability of work content (11-point scale ranging from “very stable” to ·         “ever-changing” ·         correlation matrix ·         Harman one-factor test as a preliminary analysis
37)	Omar, Z., Krauss, S.E., Sail, R.M., and Ismail, I.F. (2011)., Exploring career success of late bloomers from the TVET background. Education & Training, 53(7), 603-624	·         both quantitative and qualitative approaches ·         Survey data: 86 TVET graduate late bloomers ·         seven-point scale format (likert scale) ·         semi-structured interview protocol ·         Data analysis using SPSS ·         Descriptive analysis ·         one-way ANOVA ·         Spearman’s rank-order correlation test ·         Qualitative data analysis using a basic thematic analysis approach.