메뉴 건너뛰기




Volumn 22, Issue 4, 1997, Pages 361-387

Defining Johnson-Neyman regions of significance in the three-covariate ANCOVA using mathematica

Author keywords

Johnson Neyman ANCOVA; Mathematica; Nonhomogeneous regression

Indexed keywords


EID: 0031371869     PISSN: 10769986     EISSN: None     Source Type: Journal    
DOI: 10.3102/10769986022004361     Document Type: Article
Times cited : (14)

References (36)
  • 3
    • 18244401511 scopus 로고
    • A worksheet for the Johnson-Neyman technique
    • Butsch, R. L. C. (1944). A worksheet for the Johnson-Neyman technique. Journal of Experimental Education, 12, 226-241.
    • (1944) Journal of Experimental Education , vol.12 , pp. 226-241
    • Butsch, R.L.C.1
  • 5
    • 18244386859 scopus 로고
    • An interactive-computer program for the Johnson-Neyman technique in the case of two groups, two predictor variables, and one criterion variable
    • Carroll, J. B., & Wilson, G. F. (1970). An interactive-computer program for the Johnson-Neyman technique in the case of two groups, two predictor variables, and one criterion variable. Educational and Psychological Measurement, 30, 121-132.
    • (1970) Educational and Psychological Measurement , vol.30 , pp. 121-132
    • Carroll, J.B.1    Wilson, G.F.2
  • 10
    • 18244362215 scopus 로고
    • Using Mathematica to solve Johnson-Neyman problems
    • Hunka, S. (1994). Using Mathematica to solve Johnson-Neyman problems. Mathematica in Education, 3(3), 32-36.
    • (1994) Mathematica in Education , vol.3 , Issue.3 , pp. 32-36
    • Hunka, S.1
  • 11
    • 85004766156 scopus 로고
    • Identifying regions of significance in ANCOVA problems having non-homogeneous regressions
    • Hunka, S. (1995). Identifying regions of significance in ANCOVA problems having non-homogeneous regressions. British Journal of Mathematical and Statistical Psychology, 48, 161-188.
    • (1995) British Journal of Mathematical and Statistical Psychology , vol.48 , pp. 161-188
    • Hunka, S.1
  • 12
    • 18244370646 scopus 로고
    • The Johnson-Neyman technique, its theory and application
    • Johnson, P. O., & Fay, L. C. (1950). The Johnson-Neyman technique, its theory and application. Psychometrika, 15, 349-367.
    • (1950) Psychometrika , vol.15 , pp. 349-367
    • Johnson, P.O.1    Fay, L.C.2
  • 13
    • 84911521393 scopus 로고
    • On determining three dimensional regions of significance
    • Johnson, P. O., & Hoyt, C. (1947). On determining three dimensional regions of significance. Journal of Experimental Education, 15, 342-353.
    • (1947) Journal of Experimental Education , vol.15 , pp. 342-353
    • Johnson, P.O.1    Hoyt, C.2
  • 15
    • 0002074493 scopus 로고
    • Tests of certain linear hypotheses and their application to some educational problems
    • Johnson, P. O., & Neyman, J. (1936). Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs, 1, 57-93.
    • (1936) Statistical Research Memoirs , vol.1 , pp. 57-93
    • Johnson, P.O.1    Neyman, J.2
  • 16
    • 84965903877 scopus 로고
    • ANCOVA - A one covariate Johnson-Neyman algorithm
    • Karpman, M. B. (1980). ANCOVA - A one covariate Johnson-Neyman algorithm. Educational and Psychological Measurement, 40, 791-793.
    • (1980) Educational and Psychological Measurement , vol.40 , pp. 791-793
    • Karpman, M.B.1
  • 18
    • 84973837218 scopus 로고
    • Comparing two non-parallel regression lines with the parametric alternative to analysis of covariance using SPSS-X or SAS - The Johnson-Neyman technique
    • Karpman, M. B. (1986). Comparing two non-parallel regression lines with the parametric alternative to analysis of covariance using SPSS-X or SAS - The Johnson-Neyman technique. Educational and Psychological Measurement, 46, 639-644.
    • (1986) Educational and Psychological Measurement , vol.46 , pp. 639-644
    • Karpman, M.B.1
  • 19
    • 0003868165 scopus 로고
    • Pacific Grove, CA: Brooks/Cole
    • Kirk, R. E. (1982). Experimental design. Pacific Grove, CA: Brooks/Cole.
    • (1982) Experimental Design
    • Kirk, R.E.1
  • 20
    • 18244405643 scopus 로고
    • Steps for the application of the Johnson-Neyman technique - A sample analysis
    • Koenker, R. H., & Hansen, C. W. (1942). Steps for the application of the Johnson-Neyman technique - A sample analysis. Journal of Experimental Education, 10, 164-173.
    • (1942) Journal of Experimental Education , vol.10 , pp. 164-173
    • Koenker, R.H.1    Hansen, C.W.2
  • 21
    • 84973816347 scopus 로고
    • A Fortran V IBM computer program for the Johnson-Neyman technique
    • Kush, J. C. (1986). A Fortran V IBM computer program for the Johnson-Neyman technique. Educational and Psychological Measurement, 46, 185-187.
    • (1986) Educational and Psychological Measurement , vol.46 , pp. 185-187
    • Kush, J.C.1
  • 22
    • 84965917359 scopus 로고
    • JOHN-NEY: An interactive program for computing the Johnson-Neyman confidence region for nonsignificant prediction differences
    • Lautenschlager, G. J. (1987). JOHN-NEY: An interactive program for computing the Johnson-Neyman confidence region for nonsignificant prediction differences. Applied Psychological Measurement, 11, 194-195.
    • (1987) Applied Psychological Measurement , vol.11 , pp. 194-195
    • Lautenschlager, G.J.1
  • 29
    • 0003005101 scopus 로고
    • On the relationship between the Johnson-Neyman region of significance and statistical tests of parallel within-group regressions
    • Rogosa, D. (1981). On the relationship between the Johnson-Neyman region of significance and statistical tests of parallel within-group regressions. Educational and Psychological Measurement, 41, 73-84.
    • (1981) Educational and Psychological Measurement , vol.41 , pp. 73-84
    • Rogosa, D.1
  • 31
    • 85033278361 scopus 로고
    • Graphical description of Johnson-Neyman outcomes for linear and quadratic regression surfaces
    • April. Paper presented Chicago
    • Schafer, W. D., & Wang, Y. (1991, April). Graphical description of Johnson-Neyman outcomes for linear and quadratic regression surfaces. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago.
    • (1991) Annual Meeting of the American Educational Research Association
    • Schafer, W.D.1    Wang, Y.2
  • 34
    • 0040408219 scopus 로고
    • Some computational and model equivalences in analysis of variance of unequal-subclass-numbers data
    • Searle, S. R., Speed, F. M., & Henderson, H. V. (1981). Some computational and model equivalences in analysis of variance of unequal-subclass-numbers data. The American Statistician, 35(1), 16-33.
    • (1981) The American Statistician , vol.35 , Issue.1 , pp. 16-33
    • Searle, S.R.1    Speed, F.M.2    Henderson, H.V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.