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Year 2019, Volume: 8 Issue: 1, 24 - 61, 14.06.2019

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References

  • Adelson, J. L. (2013). Educational research with real-world data: Reducing selection bias with propensity scores. Practical Assessment, Research & Evaluation, 18(15), 2. 5 Mart 2018 tarihinde http://www.pareonline.net/getvn.asp?v=18&n=15 adresinden erişilmiştir.
  • Austin, P. C. (2011). A tutorial and case study in propensity score analysis: An application to estimating the effect of in-hospital smoking cessation counseling on mortality. Multivariate Behavioral Research, 46(1), 119-151. DOI: 10.1080/00273171.2011.540480
  • Barth, R. P., Guo, S., & McCrae, J. S. (2008). Propensity score matching strategies for evaluating the success of child and family service programs. Research on Social Work Practice, 18(3), 212-222. DOI: 10.1177/1049731507307791
  • Baser, O. (2006). Too much ado about propensity score models? Comparing methods of propensity score matching. Value in Health, 9(6), 377-385. DOI:10.1111/j.1524-4733.2006.00130.x
  • Bridgewater, F. D. (2013). The effects of school type on kindergarten reading achievement: Comparing multiple regression to propensity score matching (Yayımlanmamış Yüksek Lisans Tezi). University of Wisconsin-Milwaukee.
  • Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31-72. DOI:10.1111/j.1467-6419.2007.00527.x
  • Hahs-Vaughn, D. L., & Onwuegbuzie, A. J. (2006). Estimating and using propensity score analysis with complex samples. The Journal of Experimental Education, 75(1), 31-65. 1 Eylül 2018 tarihinde https://www.jstor.org/stable/pdf/20157441.pdf adresinden erişilmiştir.
  • Dehejia, R. H., & Wahba, S. (1999). Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs. Journal of the American statistical Association, 94(448), 1053-1062. 17 Haziran 2018 tarihinde https://www.jstor.org/stable/pdf/2669919.pdf adresinden erişilmiştir.
  • Dronkers, J., & Avram, S. (2009). Choice and effectiveness of private and public schools in seven countries. A reanalysis of three PISA data sets. Zeitschrift für Pädagogik, 55(6), 895-909.
  • Dronkers, J., & Robert, P. (2008a). Differences in scholastic achievement of public, private government-dependent, and private independent schools: A cross-national analysis. Educational Policy, 22(4), 541-577. DOI:10.1177/0895904807307065
  • Dronkers, J., & Robert, P. (2008b). School choice in the light of the effectiveness differences of various types of public and private schools in 19 OECD countries. Journal of School Choice, 2(3), 260-301. 23 Mayıs 2018 tarihinde https://mpra.ub.uni-muenchen.de/21888/1/MPRA_paper_21888.pdf adresinden erişilmiştir.
  • Fan, X., & Nowell, D. L. (2011). Using propensity score matching in educational research. Gifted Child Quarterly, 55(1), 74-79. DOI: 10.1177/00169862103906
  • Graesser, A. C. (2009). Inaugural editorial for Journal of Educational Psychology. Journal of Educational Psychology, 101, 259-261. DOI: 10.1037/a0014883
  • Grunwald, H. E., & Mayhew, M. J. (2008). Using propensity scores for estimating causal effects: A study in the development of moral reasoning. Research in Higher Education, 49(8), 758-775. DOI:10.1007/s11162-008-9103-x
  • Guo, S., & Fraser, M. W. (2010). Propensity score analysis: Statistical methods and analysis. Oaks, CA: Sage Publications.
  • Hair, M. D. (2015). Propensity score matching in SPSS: How to turn an audit into a RCT. 12 Nisan 2018 tarihinde http://www.spssusers.co.uk/Events/2015/HAIR2015.pdf adresinden erişildi.
  • Heckman, J. J. (1978). Dummy endogenous variables in a simultaneous equations system. Econometrica, 46(4), 931-959.
  • Hirano, K., & Imbens, G. W. (2001). Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization. Health Services and Outcome Methodology, 2, 259–278. 14 Mart 2018 tarhinde https://link.springer.com/content/pdf/10.1023/A:1020371312283.pdf adresinden erişildi.
  • Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political analysis, 15(3), 199-236. 27 Mart 2018 tarihinde https://www.jstor.org/stable/pdf/25791893.pdf adresinden erişildi.
  • Jiang, F., & McComas, W. F. (2015). The effects of inquiry teaching on student science achievement and attitudes: Evidence from propensity score analysis of PISA data. International Journal of Science Education, 37(3), 554-576. DOI:10.1080/09500693.2014.1000426
  • Koğar, H. (2015). PISA 2012 Matematik okuryazarlığını etkileyen faktörlerin aracılık modeli ile incelenmesi. Eğitim ve Bilim, 40(179), 45-55. DOI:10.15390/EB.2015.4445
  • Lane, F. C., To, Y. M., & Shelley, K. (2012). An illustrative example of propensity score matching with education research. Career and Technical Education Research, 37(3), 187-212. DOI: 10.5328/cter37.3.187
  • Lee, D. (2010). The early socioeconomic effects of teenage childbearing: A propensity score matching approach. Demographic Research, 23, 697-736. DOI: 10.4054/DemRes.2010.23.25
  • Levine, D. I., & Painter, G. (2003). The schooling costs of teenage out-of-wedlock childbearing: Analysis with a within-school propensity-score-matching estimator. Review of Economics and Statistics, 85(4), 884-900. 16 Mayıs 2018 tarihinde https://www.jstor.org/stable/pdf/3211812.pdf adresinden erişilmiştir.
  • Luellen, J. K., Shadish, W. R., & Clark, M. H. (2005). Propensity scores: An introduction and experimental test. Evaluation Review, 29(6), 530-558. DOI: 10.1177/0193841X05275596
  • Lunceford, J. K., & Davidian, M. (2004). Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study. Statistics in Medicine, 23, 2937-2960. DOI:10.1002/sim.1903
  • Newgard, C. D., Hedges, J. R., Arthur, M., & Mullins, R. J. (2004). Advanced statistics: The propensity score—a method for estimating treatment effect in observational research. Academic Emergency Medicine, 11(9), 953-961. DOI:10.1197/j.aem.2004.02.530
  • Nguyen, A. N., Taylor, J., & Bradley, S. (2006). The estimated effect of Catholic schooling on educational outcomes using propensity score matching. Bulletin of Economic Research, 58(4), 285-307. DOI:10.1111/j.0307-3378.2006.00245.x
  • OECD (2013). PISA 2012 results: Excellence through equity: Giving every student the chance to succeed. OECD publishing.
  • OECD (2017). PISA 2015 technical report. OECD publishing.Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55.
  • Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American statistical Association, 79(387), 516-524.
  • Rosenbaum, P. R. & Rubin, D. B. (1985). Constructing a control group using ultivariate matched sampling methods that ıncorporate the propensity score. The American Statistician, 39(1), 33–38.
  • Rosenbaum, P. R. (2002). Observational studies. In Observational studies (pp. 1-17). Springer, New York, NY. 7 Şubat 2018 tarihinde http://propensityscoreanalysis.pbworks.com/f/BehStatObserv.study.rosenbaum05.pdf adresinden erişilmiştir.
  • Rubin, D. B. (1997). Estimating causal effects from large data sets using propensity scores. Annals of Internal Medicine, 127(8S), 757-763.
  • Rubin, D. B. (2001). Using propensity scores to help design observational studies: Application to the tobacco litigation. Health Services and Outcomes Research Methodology, 2, 169-188. 17 Haziran 2018 tarihinde https://link.springer.com/content/pdf/10.1023/A:1020363010465.pdf adresinden erişilmiştir.
  • Rubin, D. B. (2007). The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Statistics in medicine, 26(1), 20-36. DOI: 10.1002/sim.2739
  • Shadish, W. R., Clark, M. H., & Steiner, P. M. (2008). Can nonrandomized experiments yield accurate answers? A randomized experiment comparing random and nonrandom assignments. Journal of the American Statistical Association, 103(484), 1334-1344. 22 Temmuz 2018 tarihinde https://www.jstor.org/stable/pdf/27640186.pdf adresinden erişilmiştir.
  • Thoemmes, F. (2012). Propensity score matching in SPSS. arXiv preprint arXiv:1201.6385. 5 Şubat 2018 tarihinde https://arxiv.org/ftp/arxiv/papers/1201/1201.6385.pdf adresinden erişilmiştir.
  • Thoemmes, F. J., & Kim, E. S. (2011). A systematic review of propensity score methods in the social sciences. Multivariate Behavioral Research, 46(1), 90-118. DOI:10.1080/00273171.2011.540475
  • Titus, M. A. (2007). Detecting selection bias, using propensity score matching, and estimating treatment effects: An application to the private returns to a master’s degree. Research in Higher Education, 48(4), 487-521. 14 Mart 2018 tarihinde https://link.springer.com/article/10.1007/s11162-006-9034-3#Sec16 adresinden erişilmiştir.
  • U.S. Department of Education, Institute of Educational Sciences. (2003). Identifying and implementing educational practices supported by rigorous evidence: A user friendly guide. Washington, DC: Institute of Education Sciences.
  • Vandenberghe, V. & Robin, S. (2003). Private, private government-dependent and public schools. An international efficiency analysis using propensity score matching. Public Economics. 19 Nisan 2018 tarihinde http://econwpa.repec.org/eps/pe/papers/0308/0308002.pdf adresinden erişilmiştir.

Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması

Year 2019, Volume: 8 Issue: 1, 24 - 61, 14.06.2019

Abstract

Eğitim
araştırmalarında önemli sorunları incelemek için rastgele atama yöntemlerinin
kullanıldığı deneysel araştırmalar çoğu zaman mümkün olmamakta veya etik
sorunlar nedeniyle tercih edilmemektedir. Bu nedenle eğitim araştırmalarında
genellikle büyük ölçekli ikincil veri setleri gibi gözlemsel veriler
kullanılmaktadır. Eğilim puanı, rastgele atanmanın olası olmadığı durumlarda
kullanılan veya gözlemsel verilerden nedensel sonuçlar elde etmek için
geliştirilmiş bir koşullu olasılıktır. Eğilim puanı eşleştirmesi, karşılaştırma
analizindeki grupları istatistiksel olarak daha fazla eşdeğer hale getirmek
için kullanılmaktadır. Bu analiz ile çok sayıda işlem öncesi ortak değişken tek
bir skaler fonksiyona indirgenmekte ve araştırmacılara işlem etkisini
belirlemede daha karşılaştırılabilir gruplar sağlamaktadır. Bu makalede (a)
eğilim puanı eşleştirme analizinin metodolojisi anlatılmış ve (b) PISA 2015
Türkiye örneklemi üzerinden elde edilen veriler yardımıyla eğilim puanı
eşleştirmesinin eğitim araştırmalarında kullanımını gösteren bir örnek sunulmuştur.
Araştırmanın sonucunda eğilim puanı eşleştirmesi ile grupların daha
karşılaştırılabilir bir duruma getirildiği belirlenmiştir. Eğilim puanı
eşleştirmesi öncesinde karşılaştırılan gruplar (özel ve devlet okulunda öğrenim
görme) okuryazarlık puanları bakımından anlamlı farklılıklar gösterirken
eşleştirme öncesi sonrasında gruplar arasında okuryazarlık puanları arasında
anlamlı farklılık bulunmamıştır. Eğilim puanı eşleştirmesi, regresyon temelli
yöntemlerin varsayımlarının karşılanmadığı durumlarda da kullanılabildiğinden
eğitim araştırmalarında bu analiz yöntemine daha fazla yer verilmesi
önerilmektedir.

References

  • Adelson, J. L. (2013). Educational research with real-world data: Reducing selection bias with propensity scores. Practical Assessment, Research & Evaluation, 18(15), 2. 5 Mart 2018 tarihinde http://www.pareonline.net/getvn.asp?v=18&n=15 adresinden erişilmiştir.
  • Austin, P. C. (2011). A tutorial and case study in propensity score analysis: An application to estimating the effect of in-hospital smoking cessation counseling on mortality. Multivariate Behavioral Research, 46(1), 119-151. DOI: 10.1080/00273171.2011.540480
  • Barth, R. P., Guo, S., & McCrae, J. S. (2008). Propensity score matching strategies for evaluating the success of child and family service programs. Research on Social Work Practice, 18(3), 212-222. DOI: 10.1177/1049731507307791
  • Baser, O. (2006). Too much ado about propensity score models? Comparing methods of propensity score matching. Value in Health, 9(6), 377-385. DOI:10.1111/j.1524-4733.2006.00130.x
  • Bridgewater, F. D. (2013). The effects of school type on kindergarten reading achievement: Comparing multiple regression to propensity score matching (Yayımlanmamış Yüksek Lisans Tezi). University of Wisconsin-Milwaukee.
  • Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31-72. DOI:10.1111/j.1467-6419.2007.00527.x
  • Hahs-Vaughn, D. L., & Onwuegbuzie, A. J. (2006). Estimating and using propensity score analysis with complex samples. The Journal of Experimental Education, 75(1), 31-65. 1 Eylül 2018 tarihinde https://www.jstor.org/stable/pdf/20157441.pdf adresinden erişilmiştir.
  • Dehejia, R. H., & Wahba, S. (1999). Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs. Journal of the American statistical Association, 94(448), 1053-1062. 17 Haziran 2018 tarihinde https://www.jstor.org/stable/pdf/2669919.pdf adresinden erişilmiştir.
  • Dronkers, J., & Avram, S. (2009). Choice and effectiveness of private and public schools in seven countries. A reanalysis of three PISA data sets. Zeitschrift für Pädagogik, 55(6), 895-909.
  • Dronkers, J., & Robert, P. (2008a). Differences in scholastic achievement of public, private government-dependent, and private independent schools: A cross-national analysis. Educational Policy, 22(4), 541-577. DOI:10.1177/0895904807307065
  • Dronkers, J., & Robert, P. (2008b). School choice in the light of the effectiveness differences of various types of public and private schools in 19 OECD countries. Journal of School Choice, 2(3), 260-301. 23 Mayıs 2018 tarihinde https://mpra.ub.uni-muenchen.de/21888/1/MPRA_paper_21888.pdf adresinden erişilmiştir.
  • Fan, X., & Nowell, D. L. (2011). Using propensity score matching in educational research. Gifted Child Quarterly, 55(1), 74-79. DOI: 10.1177/00169862103906
  • Graesser, A. C. (2009). Inaugural editorial for Journal of Educational Psychology. Journal of Educational Psychology, 101, 259-261. DOI: 10.1037/a0014883
  • Grunwald, H. E., & Mayhew, M. J. (2008). Using propensity scores for estimating causal effects: A study in the development of moral reasoning. Research in Higher Education, 49(8), 758-775. DOI:10.1007/s11162-008-9103-x
  • Guo, S., & Fraser, M. W. (2010). Propensity score analysis: Statistical methods and analysis. Oaks, CA: Sage Publications.
  • Hair, M. D. (2015). Propensity score matching in SPSS: How to turn an audit into a RCT. 12 Nisan 2018 tarihinde http://www.spssusers.co.uk/Events/2015/HAIR2015.pdf adresinden erişildi.
  • Heckman, J. J. (1978). Dummy endogenous variables in a simultaneous equations system. Econometrica, 46(4), 931-959.
  • Hirano, K., & Imbens, G. W. (2001). Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization. Health Services and Outcome Methodology, 2, 259–278. 14 Mart 2018 tarhinde https://link.springer.com/content/pdf/10.1023/A:1020371312283.pdf adresinden erişildi.
  • Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political analysis, 15(3), 199-236. 27 Mart 2018 tarihinde https://www.jstor.org/stable/pdf/25791893.pdf adresinden erişildi.
  • Jiang, F., & McComas, W. F. (2015). The effects of inquiry teaching on student science achievement and attitudes: Evidence from propensity score analysis of PISA data. International Journal of Science Education, 37(3), 554-576. DOI:10.1080/09500693.2014.1000426
  • Koğar, H. (2015). PISA 2012 Matematik okuryazarlığını etkileyen faktörlerin aracılık modeli ile incelenmesi. Eğitim ve Bilim, 40(179), 45-55. DOI:10.15390/EB.2015.4445
  • Lane, F. C., To, Y. M., & Shelley, K. (2012). An illustrative example of propensity score matching with education research. Career and Technical Education Research, 37(3), 187-212. DOI: 10.5328/cter37.3.187
  • Lee, D. (2010). The early socioeconomic effects of teenage childbearing: A propensity score matching approach. Demographic Research, 23, 697-736. DOI: 10.4054/DemRes.2010.23.25
  • Levine, D. I., & Painter, G. (2003). The schooling costs of teenage out-of-wedlock childbearing: Analysis with a within-school propensity-score-matching estimator. Review of Economics and Statistics, 85(4), 884-900. 16 Mayıs 2018 tarihinde https://www.jstor.org/stable/pdf/3211812.pdf adresinden erişilmiştir.
  • Luellen, J. K., Shadish, W. R., & Clark, M. H. (2005). Propensity scores: An introduction and experimental test. Evaluation Review, 29(6), 530-558. DOI: 10.1177/0193841X05275596
  • Lunceford, J. K., & Davidian, M. (2004). Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study. Statistics in Medicine, 23, 2937-2960. DOI:10.1002/sim.1903
  • Newgard, C. D., Hedges, J. R., Arthur, M., & Mullins, R. J. (2004). Advanced statistics: The propensity score—a method for estimating treatment effect in observational research. Academic Emergency Medicine, 11(9), 953-961. DOI:10.1197/j.aem.2004.02.530
  • Nguyen, A. N., Taylor, J., & Bradley, S. (2006). The estimated effect of Catholic schooling on educational outcomes using propensity score matching. Bulletin of Economic Research, 58(4), 285-307. DOI:10.1111/j.0307-3378.2006.00245.x
  • OECD (2013). PISA 2012 results: Excellence through equity: Giving every student the chance to succeed. OECD publishing.
  • OECD (2017). PISA 2015 technical report. OECD publishing.Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55.
  • Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American statistical Association, 79(387), 516-524.
  • Rosenbaum, P. R. & Rubin, D. B. (1985). Constructing a control group using ultivariate matched sampling methods that ıncorporate the propensity score. The American Statistician, 39(1), 33–38.
  • Rosenbaum, P. R. (2002). Observational studies. In Observational studies (pp. 1-17). Springer, New York, NY. 7 Şubat 2018 tarihinde http://propensityscoreanalysis.pbworks.com/f/BehStatObserv.study.rosenbaum05.pdf adresinden erişilmiştir.
  • Rubin, D. B. (1997). Estimating causal effects from large data sets using propensity scores. Annals of Internal Medicine, 127(8S), 757-763.
  • Rubin, D. B. (2001). Using propensity scores to help design observational studies: Application to the tobacco litigation. Health Services and Outcomes Research Methodology, 2, 169-188. 17 Haziran 2018 tarihinde https://link.springer.com/content/pdf/10.1023/A:1020363010465.pdf adresinden erişilmiştir.
  • Rubin, D. B. (2007). The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Statistics in medicine, 26(1), 20-36. DOI: 10.1002/sim.2739
  • Shadish, W. R., Clark, M. H., & Steiner, P. M. (2008). Can nonrandomized experiments yield accurate answers? A randomized experiment comparing random and nonrandom assignments. Journal of the American Statistical Association, 103(484), 1334-1344. 22 Temmuz 2018 tarihinde https://www.jstor.org/stable/pdf/27640186.pdf adresinden erişilmiştir.
  • Thoemmes, F. (2012). Propensity score matching in SPSS. arXiv preprint arXiv:1201.6385. 5 Şubat 2018 tarihinde https://arxiv.org/ftp/arxiv/papers/1201/1201.6385.pdf adresinden erişilmiştir.
  • Thoemmes, F. J., & Kim, E. S. (2011). A systematic review of propensity score methods in the social sciences. Multivariate Behavioral Research, 46(1), 90-118. DOI:10.1080/00273171.2011.540475
  • Titus, M. A. (2007). Detecting selection bias, using propensity score matching, and estimating treatment effects: An application to the private returns to a master’s degree. Research in Higher Education, 48(4), 487-521. 14 Mart 2018 tarihinde https://link.springer.com/article/10.1007/s11162-006-9034-3#Sec16 adresinden erişilmiştir.
  • U.S. Department of Education, Institute of Educational Sciences. (2003). Identifying and implementing educational practices supported by rigorous evidence: A user friendly guide. Washington, DC: Institute of Education Sciences.
  • Vandenberghe, V. & Robin, S. (2003). Private, private government-dependent and public schools. An international efficiency analysis using propensity score matching. Public Economics. 19 Nisan 2018 tarihinde http://econwpa.repec.org/eps/pe/papers/0308/0308002.pdf adresinden erişilmiştir.
There are 42 citations in total.

Details

Primary Language Turkish
Journal Section Makaleler
Authors

Esin Yılmaz Koğar 0000-0001-6755-9018

Publication Date June 14, 2019
Published in Issue Year 2019 Volume: 8 Issue: 1

Cite

APA Yılmaz Koğar, E. (2019). Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması. Amasya Üniversitesi Eğitim Fakültesi Dergisi, 8(1), 24-61.
AMA Yılmaz Koğar E. Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması. Amasya Üniversitesi Eğitim Fakültesi Dergisi. June 2019;8(1):24-61.
Chicago Yılmaz Koğar, Esin. “Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması”. Amasya Üniversitesi Eğitim Fakültesi Dergisi 8, no. 1 (June 2019): 24-61.
EndNote Yılmaz Koğar E (June 1, 2019) Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması. Amasya Üniversitesi Eğitim Fakültesi Dergisi 8 1 24–61.
IEEE E. Yılmaz Koğar, “Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması”, Amasya Üniversitesi Eğitim Fakültesi Dergisi, vol. 8, no. 1, pp. 24–61, 2019.
ISNAD Yılmaz Koğar, Esin. “Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması”. Amasya Üniversitesi Eğitim Fakültesi Dergisi 8/1 (June 2019), 24-61.
JAMA Yılmaz Koğar E. Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması. Amasya Üniversitesi Eğitim Fakültesi Dergisi. 2019;8:24–61.
MLA Yılmaz Koğar, Esin. “Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması”. Amasya Üniversitesi Eğitim Fakültesi Dergisi, vol. 8, no. 1, 2019, pp. 24-61.
Vancouver Yılmaz Koğar E. Eğilim Puanı Eşleştirme Analizinin Eğitim Araştırmalarında Kullanılması. Amasya Üniversitesi Eğitim Fakültesi Dergisi. 2019;8(1):24-61.

Amasya Üniversitesi Eğitim Fakültesi Dergisi (Amasya Education Journal)