Blom, R., Kruyen, P. M., Van der Heijden, B. I., & Van Thiel, S. (2020). One HRM fits all? A meta-analysis of the effects of HRM practices in the public, semipublic, and private sector. Review of Public Personnel Administration, 40(1), 3–35.
Borenstein, M. (2009). Effect sizes for continuous data. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (2nd ed., pp. 221–236). Russell Sage.
Cheung, M. W. L. (2015). Meta-analysis: A structural equation modeling approach. John Wiley & Sons.
Chalmers, I., Hedges, L. V., & Cooper, H. (2002). A brief history of research synthesis. Evaluation & the Health Professions, 25(1), 12–37.
Chapman, C. M., Hornsey, M. J., & Gillespie, N. (2021). To what extent is trust a prerequisite for charitable giving? A systematic review and meta-analysis. Nonprofit and Voluntary Sector Quarterly, 50, 1274–1303. https://doi.org/10.1177/08997640211003250
Cooper, H. (2017). Research synthesis and meta-analysis: A step-by-step approach. Sage.
Daniel, J. L., & Kim, M. (2018). The scale of mission-embeddedness as a nonprofit revenue classification tool: Different earned revenue types, different performance effects. Administration & Society, 50(7), 947–972.
De Wit, A., & Bekkers, R. (2017). Government support and charitable donations: A meta-analysis of the crowding-out hypothesis. Journal of Public Administration Research and Theory, 27(2), 301–319.
Fleiss, J. L., & Berlin, J. A. (2009). Effect sizes for dichotomous data. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (2nd ed., pp. 237–254). Russell Sage.
Geyskens, I., Krishnan, R., Steenkamp, J. B. E., & Cunha, P. V. (2009). A review and evaluation of meta-analysis practices in management research. Journal of Management, 35(2), 393–419.
Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8.
Gurevitch, J., Koricheva, J., Nakagawa, S., & Stewart, G. (2018). Meta-analysis and the science of research synthesis. Nature, 555(7695), 175–182.
Hedges, L., & Olkin, I. (1985). Statistical methods for meta-analysis. Academic Press.
Hung, C. (2020). Commercialization and nonprofit donations: A meta-analytic assessment and extension. Nonprofit Management and Leadership. https://doi.org/10.1002/nml.21435
Hung, C., & Hager, M. A. (2019). The impact of revenue diversification on nonprofit financial health: A meta-analysis. Nonprofit and Voluntary Sector Quarterly, 48(1), 5–27.
Hunt, M. (1997). How science takes stock: The story of meta-analysis. Russell Sage Foundation.
Jackson, S. K., Guerrero, S., & Appe, S. (2014). The state of nonprofit and philanthropic studies doctoral education. Nonprofit and Voluntary Sector Quarterly, 43(5), 795–811.
Kim, M. (2017). The relationship of nonprofits’ financial health to program outcomes: Empirical evidence from nonprofit arts organizations. Nonprofit and Voluntary Sector Quarterly, 46(3), 525–548.
Kulik, J. A., & Kulik, C. L. C. (1989). Meta-analysis in education. International Journal of Educational Research, 13(3), 221–340.
Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Sage.
Lu, J. (2016). The philanthropic consequence of government grants to nonprofit organizations: A meta-analysis. Nonprofit Management and Leadership, 26(4), 381–400.
Lu, J. (2017). Does population heterogeneity really matter to nonprofit sector size? Revisiting Weisbrod’s demand heterogeneity hypothesis. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 1–27.
Lu, J. (2018). Organizational antecedents of nonprofit engagement in policy advocacy: A meta-analytical review. Nonprofit and Voluntary Sector Quarterly, 47(4_suppl), 177S-203S.
Lu, J., & Xu, C. (2018). Complementary or supplementary? The relationship between government size and nonprofit sector size. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 29(3), 454–469.
Lu, J., Lin, W., & Wang, Q. (2019). Does a more diversified revenue structure lead to greater financial capacity and less vulnerability in nonprofit organizations? A bibliometric and meta-analysis. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 30(3), 593–609.
Ma, J., & Konrath, S. (2018). A century of nonprofit studies: Scaling the knowledge of the field. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 29(6), 1139–1158.
Pearson, K. (1904). Report on certain enteric fever inoculation statistics. BMJ, 3, 1243–1246.
Pfeffer, J. (1993). Barriers to the advance of organizational science: Paradigm development as a dependent variable. Academy of Management Review, 18(4), 599–620.
Reed, J. G., & Baxter, P. M. (2009). Using reference databases. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (2nd ed., pp. 73–101). Russell Sage Foundation.
Ringquist, E. (2013). Meta-analysis for public management and policy. John Wiley & Sons.
Rosethal, R., & DiMatteo, M. (2001). Meta-analysis: Recent developments in quantitative methods for literature review. Annual Review of Psychology, 52, 59–82.
Rothstein, H. R., Sutton, A. J., & Borenstein, M. (Eds.). (2006). Publication bias in meta-analysis: Prevention, assessment and adjustments. John Wiley & Sons.
Schmidt, F. L. (1992). What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology. American Psychologist, 47(10), 1173–1181.
Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings. Sage.
Shadish, W. R., & Lecy, J. D. (2015). The meta-analytic big bang. Research Synthesis Methods, 6(3), 246–264.
Shoham, A., Ruvio, A., Vigoda-Gadot, E., & Schwabsky, N. (2006). Market orientations in the nonprofit and voluntary sector: A meta-analysis of their relationships with organizational performance. Nonprofit and Voluntary Sector Quarterly, 35(3), 453–476.
Smith, M. L., & Glass, G. V. (1977). Meta-analysis of psychotherapy outcome studies. American Psychologist, 32(9), 752–760.
Stanley, T. D., & Jarrell, S. B. (2005). Meta-regression analysis: A quantitative method of literature surveys. Journal of Economic Surveys, 19(3), 299–308.
Sutton, A. J. (2009). Publication bias. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (2nd ed., pp. 435–452). Russell Sage Foundation.
Sutton, A. J., Abrams, K. R., Jones, D. R., Jones, D. R., Sheldon, T. A., & Song, F. (2000). Methods for meta-analysis in medical research. Wiley.
Thompson, S. G., & Higgins, J. P. (2002). How should meta-regression analyses be undertaken and interpreted? Statistics in Medicine, 21(11), 1559–1573.
Tipton, E., Pustejovsky, J. E., & Ahmadi, H. (2019). A history of meta-regression: Technical, conceptual, and practical developments between 1974 and 2018. Research Synthesis Methods, 10(2), 161–179.
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222.
Xu, J., & Huang, G. (2020). The relative effectiveness of gain-framed and loss-framed messages in charity advertising: Meta-analytic evidence and implications. International Journal of Nonprofit and Voluntary Sector Marketing, 25(4), e1675.
Willems, J., Boenigk, S., & Jegers, M. (2014). Seven trade-offs in measuring nonprofit performance and effectiveness. Voluntas: International Journal of Voluntary and Nonprofit Organizations, 25(6), 1648–1670.