Sample sizes for social science surveys and impact on knowledge generation
DOI:
https://doi.org/10.29105/rinn11.22-4Keywords:
confidence intervals, Cronbach's alpha, effect size, factor analysis, hypothesis testing, sample size, structural equation modelingAbstract
The purpose of this paper is to contribute to fulfilling the objectives of social sciences research such as proper estimation, explanation, prediction and control of levels of social reality variables and their interrelationships, especially when dealing with quantitative variables. It was shown that the sample size or the number of observations to be collected and analyzed is transcendental for the adequacy of the method of statistical inference selected and for the impact degree achieved in its results, especially for complying with reports guidelines issued by the American Psychological Association. Methods and formulations were investigated to determine the sample sizes that contribute to have good levels of estimation when establishing confidence intervals, with reasonable wide and relevant and significative magnitudes of the effects. Practical rules suggested by several researchers when determining samples sizes were tested and as a result it was integrated a guide for determining sample sizes for dichotomous, continuous, discrete and Likert variables, correlation and regression methods, factor analysis, Cronbach's alpha, and structural equation models. It is recommended that the reader builds scenarios with this guide and be aware of the implications and relevance in scientific research and decision making of the sample sizes in trying to meet the aforementioned objectives.
Downloads
References
APA, Board of Scientific Affairs. (1996). Initial Report of The Task Force on Statistical Inference. Recuperado de http://www.apa.org/science/leadership/bsa/statistical/tfsiinitial-report.pdf el 18 de Septiembre del 2014
Cervantes, V.H. (2005). Interpretaciones del coeficiente alpha de Cronbach. Avances en Medición, 3, 9-28.
Chin, W.W. (1988). Issues and opinions on structural equation modeling. Management Information Systems Quarterly, 22(1), 7-16.
Chin, W.W. (1998) Chapter 10: “The Partial Least Squares Approach for Structural Equation Modeling”, in Maroulides, G. A. (ed.). Modern Methods for Business Research, Hillsdate,N.J. : Lawrence Erlbaum Associates.
Churchill, G.A. (1991), Marketing research: Methodological foundations, 5th ed. Hinsdale, Il:Dryden Press
Cortina, J.M. (1993). What is coefficient alpha? An Examination of Theory and Applications. Journal of Applied Psychology, 78(1), 98-104
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika,16(3), 297-334.
De-la-Garza-García, J., Morales-Serrano, B.N. y González-Cavazos, B.A.(2013). Análisis Estadístico-Multivariado: Un enfoque teórico y práctico. Monterrey, México: McGrawHill.
Fidler, F., Thomason, Neil, Cumming, G. Finch, S. & Leeman, J. (2004). Editors Can Lead Researchers to Confidence Intervals, but Can’t Make Then Think: Statistical Lessons From Medicine.
Psychological Science 2004 15:119 Recuperado de http://pss.sagepub.com/content/15/2/119
Hair, J.F, Anderson, R. E., Tatham, R. L. y Black, W. C. (1999). Análisis Multivariante, 5ª. Edición. Madrid: Prentice-Hall
Hanke, J. E. & Wichern, D. W. (2010). Pronósticos en los Negocios, 9ª. Edición. México:Prentce-Hall
Havlicek, L. & Peterson, N. (1976). Robustness of the Pearson correlation against violations of assumptions, Perceptual and Motor Skills, 43(3f), 319-1334.
Jamieson, S. (2004). Likert scales: How to (ab)use them. Medical Education, 38(12), 1217-1218.
Knofczyinski, G. T. & Mundford, D. (2008). Sample sizes when using multiple linear regression for prediction. Educational and psychological measurement, 68(3), 431-442.
Lind, D. A., Marchal, W. C. & Wathen, S.A. (2012). Estadística aplicada a los negocios y la economía 15ª. Edición. México: McGraw-Hill.
Moral de la Rubia, José. (2009). Capítulo 13. Análisis factorial y su aplicación al desarrollo de escalas, en Landeros-Hernández, R. & González-Ramírez (eds.). Estadística con SPSS y metodología de la investigación, Monterrey: Trillas.
Pértegas-Díaz, S & Pita-Fernández, S. (2002). Metodología de investigación. Coruña:Fisterra.
Royer, I. & Zarlowski, P. (1999). Chap. 8. Sampling, en Thiétart, Raymond-Alain. Doing Management Research: A Comprehensive Guide. London: Sagen
Shrout, P. (1997). Should significance test be banned? Introduction to a special section exploring the pros and cons. Psychological Science, 8(1), 1-2.
Sierra-Bravo, R. (1983). Ciencias sociales. Espistemología, lógica y metodología. Teoría y ejercicios. Madrid: Paraninfo
Thiétart, A. (1999). Doing management research. London: Sage.
Wilkinson, L. (1999). The task force on statistical inference. American Psychologist, 54(8),594-604.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2017 Innovaciones de Negocios
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The InnOvaciOnes de NegOciOs magazine is a free and open access electronic magazine of a scientific-academic nature and is a publication of the Autonomous University of Nuevo León, in which the authors retain their copyright and grant the magazine the exclusive right to first publication of the work. Third parties are allowed to use the published content, as long as the authorship of the work is acknowledged and the first publication in this journal is cited.
For more information, please contact the Research Secretary (FACPyA) of the Autonomous University of Nuevo León. Telephone: (81) 1340-4430. Email: revinnova@uanl.mx
