IDEAS home Printed from https://ideas.repec.org/a/sae/evarev/v15y1991i5p625-638.html
   My bibliography  Save this article

Linear Versus Nonlinear Analysis in the Measurement of Effects in a Quasi-Experimental Design

Author

Listed:
  • Marcel W. Vooijs

    (Leiden University, Center for Child and Media Studies)

  • Leo J. Th. Van Der Kamp

    (Leiden University, Center for Child and Media Studies)

Abstract

In this study, a two-step procedure for the analysis of pretest-posttest data is developed and illustrated. In the first step, a nonlinear canonical correlation analysis was conducted on data from a pretest-posttest control group design. This technique transforms the measure of the pretests (including the scores on the treatment variable) and the posttests in such a way that they become interrelated linearly and possible deviations from the linear model due to nonlinearity have been minimized. In the second step, the resulting optimally scaled set of pretest and posttest measures were analyzed using covariance procedures to assess program effects. The resultant variance appeared to be increased substantially, either by a better prediction of posttest scores from pretest scores, by a better estimation of the effect of the treatment, or by both. It is concluded that the two-step procedure indeed has important advantages.

Suggested Citation

  • Marcel W. Vooijs & Leo J. Th. Van Der Kamp, 1991. "Linear Versus Nonlinear Analysis in the Measurement of Effects in a Quasi-Experimental Design," Evaluation Review, , vol. 15(5), pages 625-638, October.
    • Handle: RePEc:sae:evarev:v:15:y:1991:i:5:p:625-638
    DOI: 10.1177/0193841X9101500506
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0193841X9101500506
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0193841X9101500506?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Forrest Young & Jan Leeuw & Yoshio Takane, 1976. "Regression with qualitative and quantitative variables: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 41(4), pages 505-529, December.
    2. Dag Sörbom, 1978. "An alternative to the methodology for analysis of covariance," Psychometrika, Springer;The Psychometric Society, vol. 43(3), pages 381-396, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cook, Judith A. & Razzano, Lisa & Cappelleri, Joseph C., 1996. "Canonical correlation analysis of residential and vocational outcomes following psychiatric rehabilitation," Evaluation and Program Planning, Elsevier, vol. 19(4), pages 351-363, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kadziński, MiŁosz & Greco, Salvatore & SŁowiński, Roman, 2012. "Extreme ranking analysis in robust ordinal regression," Omega, Elsevier, vol. 40(4), pages 488-501.
    2. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    3. Grigoroudis, Evangelos & Noel, Laurent & Galariotis, Emilios & Zopounidis, Constantin, 2021. "An ordinal regression approach for analyzing consumer preferences in the art market," European Journal of Operational Research, Elsevier, vol. 290(2), pages 718-733.
    4. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
    5. Dagum, Camilo & Slottje, Daniel J., 2000. "A new method to estimate the level and distribution of household human capital with application," Structural Change and Economic Dynamics, Elsevier, vol. 11(1-2), pages 67-94, July.
    6. van Rosmalen, J.M. & Koning, A.J. & Groenen, P.J.F., 2007. "Optimal Scaling of Interaction Effects in Generalized Linear Models," Econometric Institute Research Papers EI 2007-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Daniel U Campos-Delgado & Omar Gutierrez-Navarro & Ricardo Salinas-Martinez & Elvis Duran & Aldo R Mejia-Rodriguez & Miguel J Velazquez-Duran & Javier A Jo, 2021. "Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-29, March.
    8. Ronald S. Burt & Michael G. Fischer & Kenneth P. Christman, 1979. "Structures of Well-Being," Sociological Methods & Research, , vol. 8(1), pages 111-120, August.
    9. Gerhard Tutz & Jan Gertheiss, 2014. "Rating Scales as Predictors—The Old Question of Scale Level and Some Answers," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 357-376, July.
    10. P. Bentler, 1986. "Structural modeling and psychometrika: An historical perspective on growth and achievements," Psychometrika, Springer;The Psychometric Society, vol. 51(1), pages 35-51, March.
    11. Hye Won Suk & Heungsun Hwang, 2016. "Functional Generalized Structured Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 940-968, December.
    12. Michio Yamamoto, 2012. "Clustering of functional data in a low-dimensional subspace," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(3), pages 219-247, October.
    13. Vittadini, Giorgio & Lovaglio, Pietro Giorgio, 2007. "Evaluation of the Dagum-Slottje method to estimate household human capital," Structural Change and Economic Dynamics, Elsevier, vol. 18(2), pages 270-278, June.
    14. Jan Leeuw & Forrest Young & Yoshio Takane, 1976. "Additive structure in qualitative data: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 41(4), pages 471-503, December.
    15. Takane, Yoshio, 2016. "My Early Interactions with Jan and Some of His Lost Papers," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 73(i07).
    16. Zhou, Lixing & Takane, Yoshio & Hwang, Heungsun, 2016. "Dynamic GSCANO (Generalized Structured Canonical Correlation Analysis) with applications to the analysis of effective connectivity in functional neuroimaging data," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 93-109.
    17. Jacquet-Lagreze, Eric & Siskos, Yannis, 2001. "Preference disaggregation: 20 years of MCDA experience," European Journal of Operational Research, Elsevier, vol. 130(2), pages 233-245, April.
    18. Seohee Park & Seongeun Kim & Ji Hoon Ryoo, 2020. "Latent Class Regression Utilizing Fuzzy Clusterwise Generalized Structured Component Analysis," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    19. Benedetto Manganelli & Pierluigi Morano & Francesco Tajani & Francesca Salvo, 2019. "Affordability Assessment of Energy-Efficient Building Construction in Italy," Sustainability, MDPI, vol. 11(1), pages 1-17, January.
    20. John C. Gower & Sugnet Gardner-Lubbe & Niel J. Le Roux, 2018. "Interaction: Fisher’s Optimal Scores Revisited," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(1), pages 92-112, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:evarev:v:15:y:1991:i:5:p:625-638. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.