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      Similarity and Contact Frequency Promote Mentorship Quality among Hispanic Undergraduates in STEM

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          Abstract

          Mentoring relationships can be important for promoting the success and persistence of undergraduates, particularly for students from historically underrepresented groups in science, technology, engineering, and mathematics (STEM) disciplines. While mentoring is often cited as important for attracting and retaining students from underrepresented groups in STEM, little is known about the differential mentoring processes that can result from similar and dissimilar mentor–protégé pairs. The present study tests the process-oriented mentorship model (POMM) regarding how mentor–protégé similarities and the moderating role of contact frequency influence mentorship quality and STEM research career persistence intentions among faculty-mentored Hispanic STEM majors in their senior year of college. The results indicate that mentor–protégé similarity matters. Specifically, higher levels of mentor–protégé psychological similarity were related to higher levels of psychosocial support and relationship satisfaction. Hispanic students with a Hispanic faculty mentor reported engaging in more coauthoring opportunities than peers with non-Hispanic mentors. Among those with higher contact frequency, students with same-gender mentors had higher levels of relationship satisfaction than peers with different-gender mentors; however, there were no differences among those with low contact frequency. Additionally, protégés who reported coauthoring support were more likely to also report commitment to pursuing a STEM research career.

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          A power primer.

          One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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            Using Multivariate Statistics

            After the Introduction Chapter, the second Chapter gives a guide to the multivariate techniques that are covered in this book and palces them in context with the more familiare univeriate and bivariate statistics where possible. Included in this chapter is a flow chart that organizes statistical techniques on the basis of the major research questions asked. Chapter three provides a brief review of univariate and bivariate statistical techniques for those who are interested. Chapter four deals with the assumptions an limitations of mulitvariate statistical methods. Assessment and violation of assumptions are discussed, along with alternatives for dealing with violations when they occur. This chapter is also meant to be referred to often, and the reader ist guided back to it frequently in Chapters five through sixteen an eighteen (online). Chapters five through sixteen and eighteen (online) cover specific multivariate techniques. They include descriptive, conceptual sections as well as a guided tour through a real-world data set for which the analysis is apporopriate. The tour includes an example of a Results section describing the outcome of the statistical analysis apporopriate for submissions to a professional journal. Each technique chapter includes a comparision of cumputer programs. Chapter seventeen is an attempt to integrate univariate, bivariate, and multivariate statistics through the multivariate general linear model. The common elements underlying all the techniques are emphasized, rather than the differences among them. This Chapter is ment to pull together the material in the remainder of the book with a conceptual rather than pragmatic emphasis.
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              Is actual similarity necessary for attraction? A meta-analysis of actual and perceived similarity

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                Author and article information

                Contributors
                Role: Monitoring Editor
                Journal
                CBE Life Sci Educ
                CBE Life Sci Educ
                CBE-LSE
                lse
                CBE Life Sciences Education
                American Society for Cell Biology
                1931-7913
                Summer 2022
                : 21
                : 2
                : ar27
                Affiliations
                []Department of Teaching, Learning, & Culture, Texas A&M University, College Station, TX 77840
                []Department of Counseling and Learning Sciences, West Virginia University, Morgantown, WV 26506
                [§ ]Department of Social and Behavioral Sciences, Institute for Health and Aging, University of California, San Francisco, San Francisco, CA 94143
                [ǁ ]Department of Psychology, California State University, San Marcos, CA 92096
                Author notes
                *Address correspondence to: Rachelle M. Pedersen ( pedersenr@ 123456tamu.edu ).

                ORCID ID: Rachelle M. Pedersen (0000-0001-8530-9071); Carinna F. Ferguson (0000-0001-5036-9103); Mica Estrada (0000-0003-3933-2929); P. Wesley Schultz (0000-0003-4098-924X); Anna Woodcock (0000-0002-9183-8516); and Paul R. Hernandez (0000-0002-4063-357X)

                Article
                CBE.21-10-0305
                10.1187/cbe.21-10-0305
                9508928
                35452264
                82d25f89-8a6d-4a0b-832c-9e0fa4c65b30
                © 2022 R. M. Pedersen et al. CBE—Life Sciences Education © 2022 The American Society for Cell Biology. “ASCB®” and “The American Society for Cell Biology®” are registered trademarks of The American Society for Cell Biology.

                This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 4.0 Unported Creative Commons License.

                History
                : 20 October 2021
                : 14 February 2022
                : 10 March 2022
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