Academic Journal
Statistical power of likelihood ratio and Wald tests in latent class models with covariates
العنوان: | Statistical power of likelihood ratio and Wald tests in latent class models with covariates |
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المؤلفون: | Gudicha, D.W., Schmittmann, V.D., Vermunt, J.K. |
المصدر: | Gudicha , D W , Schmittmann , V D & Vermunt , J K 2017 , ' Statistical power of likelihood ratio and Wald tests in latent class models with covariates ' , Behavior Research Methods , vol. 49 , no. 5 , pp. 1824-1837 . https://doi.org/10.3758/s13428-016-0825-y |
سنة النشر: | 2017 |
المجموعة: | Tilburg University: Research portal |
مصطلحات موضوعية: | Latent class, Power analysis, Likelihood ratio, Wald test, Asymptotic distributions, Non-centrality parameter, Large simulated data set, SAMPLE-SIZE, LOGISTIC-REGRESSION, NUMBER |
الوصف: | This paper discusses power and sample-size computation for likelihood ratio and Wald testing of the significance of covariate effects in latent class models. For both tests, asymptotic distributions can be used; that is, the test statistic can be assumed to follow a central Chi-square under the null hypothesis and a non-central Chi-square under the alternative hypothesis. Power or sample-size computation using these asymptotic distributions requires specification of the non-centrality parameter, which in practice is rarely known. We show how to calculate this non-centrality parameter using a large simulated data set from the model under the alternative hypothesis. A simulation study is conducted evaluating the adequacy of the proposed power analysis methods, determining the key study design factor affecting the power level, and comparing the performance of the likelihood ratio and Wald test. The proposed power analysis methods turn out to perform very well for a broad range of conditions. Moreover, apart from effect size and sample size, an important factor affecting the power is the class separation, implying that when class separation is low, rather large sample sizes are needed to achieve a reasonable power level. |
نوع الوثيقة: | article in journal/newspaper |
وصف الملف: | application/pdf |
اللغة: | English |
DOI: | 10.3758/s13428-016-0825-y |
الاتاحة: | https://research.tilburguniversity.edu/en/publications/3783a550-2cba-4e63-b285-8d0de80e2d66 https://doi.org/10.3758/s13428-016-0825-y https://pure.uvt.nl/ws/files/19061342/MTO_Gudicha_statistical_power_BRM_open_access_2017.pdf |
Rights: | info:eu-repo/semantics/openAccess |
رقم الانضمام: | edsbas.96773A3F |
قاعدة البيانات: | BASE |
DOI: | 10.3758/s13428-016-0825-y |
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