Power analysis for the bootstrap likelihood ratio test for the number of classes in latent class models
Latent class (LC) analysis is used to construct empirical evidence on the existence of latent subgroups based on the associations among a set of observed discrete variables. One of the tests used to infer about the number of underlying subgroups is the bootstrap likelihood ratio test (BLRT). Althoug...
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| Published in | Advances in data analysis and classification Vol. 10; no. 2; pp. 209 - 224 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.06.2016
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| Online Access | Get full text |
| ISSN | 1862-5347 1862-5355 |
| DOI | 10.1007/s11634-016-0251-0 |
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| Abstract | Latent class (LC) analysis is used to construct empirical evidence on the existence of latent subgroups based on the associations among a set of observed discrete variables. One of the tests used to infer about the number of underlying subgroups is the bootstrap likelihood ratio test (BLRT). Although power analysis is rarely conducted for this test, it is important to identify, clarify, and specify the design issues that influence the statistical inference on the number of latent classes based on the BLRT. This paper proposes a computationally efficient ‘short-cut’ method to evaluate the power of the BLRT, as well as presents a procedure to determine a required sample size to attain a specific power level. Results of our numerical study showed that this short-cut method yields reliable estimates of the power of the BLRT. The numerical study also showed that the sample size required to achieve a specified power level depends on various factors of which the class separation plays a dominant role. In some situations, a sample size of 200 may be enough, while in others 2000 or more subjects are required to achieve the required power. |
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| AbstractList | Latent class (LC) analysis is used to construct empirical evidence on the existence of latent subgroups based on the associations among a set of observed discrete variables. One of the tests used to infer about the number of underlying subgroups is the bootstrap likelihood ratio test (BLRT). Although power analysis is rarely conducted for this test, it is important to identify, clarify, and specify the design issues that influence the statistical inference on the number of latent classes based on the BLRT. This paper proposes a computationally efficient ‘short-cut’ method to evaluate the power of the BLRT, as well as presents a procedure to determine a required sample size to attain a specific power level. Results of our numerical study showed that this short-cut method yields reliable estimates of the power of the BLRT. The numerical study also showed that the sample size required to achieve a specified power level depends on various factors of which the class separation plays a dominant role. In some situations, a sample size of 200 may be enough, while in others 2000 or more subjects are required to achieve the required power. |
| Author | Tekle, Fetene B. Gudicha, Dereje W. Vermunt, Jeroen K. |
| Author_xml | – sequence: 1 givenname: Fetene B. surname: Tekle fullname: Tekle, Fetene B. email: ftekle@ITS.JNJ.com organization: Department of Nonclinical Statistics and Computing, Janssen Research and Development – sequence: 2 givenname: Dereje W. surname: Gudicha fullname: Gudicha, Dereje W. organization: Department of Methodology and Statistics, Tilburg University – sequence: 3 givenname: Jeroen K. surname: Vermunt fullname: Vermunt, Jeroen K. organization: Department of Methodology and Statistics, Tilburg University |
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| Keywords | Bootstrap Latent class models Sample size 62F03 Likelihood ratio test Power |
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| References | Lo, Mendell, Rubin (CR16) 2001; 88 Davidson, MacKinnon (CR5) 2006; 133 Oberski (CR23) 2015 Johnson, Rossell (CR12) 2010; 27 Vermunt (CR34) 2010; 18 Bock (CR2) 1996; 23 CR19 CR36 Cohen (CR3) 1988 CR35 CR30 Van der Heijden, HitHart, Dessens, Rost, Langeheine (CR33) 1997 Langeheine, Pannekoek, van de Pol (CR13) 1996; 24 Magidson, Vermunt, Kaplan (CR17) 2004 Everitt (CR7) 1981; 16 McLachlan, Peel (CR20) 2000 Leask, Vermunt, Done, Crowd, Blows, Boks (CR15) 2009; 115 Self, Mauritsen, Ohara (CR27) 1992; 48 Holt, Macready (CR10) 1989; 13 Lazarsfeld, Henry (CR14) 1968 Steiger, Shapiro, Browne (CR29) 1985; 50 Zenor, Srivastava (CR38) 1993; 25 Schwarz (CR26) 1978; 6 Shapiro (CR28) 1985; 72 Tollenaar, Mooijaart (CR32) 2003; 56 Jeffries (CR11) 2003; 90 McLachlan (CR18) 1987; 36 Rindskopf (CR24) 2002 Nylund, Muthen, Muthen (CR22) 2007; 14 Akaike (CR1) 1974; 19 Dias, Vermunt (CR6) 2007; 14 Hartigan, Ryzin (CR9) 1977 CR21 Tekle, Tan, Berger (CR31) 2008; 52 Collins, Lanza (CR4) 2010 Rubin (CR25) 1981; 9 Wolfe (CR37) 1970; 5 Genge (CR8) 2014; 8 YT Lo (251_CR16) 2001; 88 251_CR30 G McLachlan (251_CR20) 2000 D Rindskopf (251_CR24) 2002 H Akaike (251_CR1) 1974; 19 SJ Leask (251_CR15) 2009; 115 VE Johnson (251_CR12) 2010; 27 A Shapiro (251_CR28) 1985; 72 JK Vermunt (251_CR34) 2010; 18 JA Holt (251_CR10) 1989; 13 JA Hartigan (251_CR9) 1977 LM Collins (251_CR4) 2010 JH Steiger (251_CR29) 1985; 50 D Oberski (251_CR23) 2015 JG Dias (251_CR6) 2007; 14 BS Everitt (251_CR7) 1981; 16 G Schwarz (251_CR26) 1978; 6 DB Rubin (251_CR25) 1981; 9 251_CR21 N Tollenaar (251_CR32) 2003; 56 J Magidson (251_CR17) 2004 HH Bock (251_CR2) 1996; 23 JH Wolfe (251_CR37) 1970; 5 PF Lazarsfeld (251_CR14) 1968 MJ Zenor (251_CR38) 1993; 25 SG Self (251_CR27) 1992; 48 J Cohen (251_CR3) 1988 FB Tekle (251_CR31) 2008; 52 251_CR19 PGM Heijden Van der (251_CR33) 1997 G McLachlan (251_CR18) 1987; 36 R Davidson (251_CR5) 2006; 133 NO Jeffries (251_CR11) 2003; 90 E Genge (251_CR8) 2014; 8 R Langeheine (251_CR13) 1996; 24 KL Nylund (251_CR22) 2007; 14 251_CR35 251_CR36 |
| References_xml | – volume: 90 start-page: 991 year: 2003 end-page: 994 ident: CR11 article-title: A note on ’testing the number of components in a normal mixture publication-title: Biometrika doi: 10.1093/biomet/90.4.991 – year: 2010 ident: CR4 publication-title: Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences – year: 2015 ident: CR23 article-title: Beyond the number of classes: separating substantive from non-substantive dependence in latent class analysis publication-title: Adv Data Anal Classif – start-page: 2912 year: 2002 end-page: 2916 ident: CR24 publication-title: The use of latent class analysis in medical diagnosis – volume: 48 start-page: 31 year: 1992 end-page: 39 ident: CR27 article-title: Power calculations for likelihood ratio tests in generalized linear models publication-title: Biometrics doi: 10.2307/2532736 – volume: 72 start-page: 133 year: 1985 end-page: 144 ident: CR28 article-title: Asymptotic distribution of test statistics in the analysis of moment structures under inequality constraints publication-title: Biometrika doi: 10.1093/biomet/72.1.133 – start-page: 190 year: 1997 end-page: 202 ident: CR33 article-title: A parametric bootstrap procedure to perform statistical tests in latent class analysis publication-title: Applications of latent trait and latent class models in the social sciences – volume: 18 start-page: 450 year: 2010 end-page: 469 ident: CR34 article-title: Latent class modeling with covariates: two improved three-step approaches publication-title: Political Anal doi: 10.1093/pan/mpq025 – volume: 19 start-page: 716 year: 1974 end-page: 723 ident: CR1 article-title: A new look at the statistical model identification publication-title: IEEE Trans Autom Control doi: 10.1109/TAC.1974.1100705 – start-page: 45 year: 1977 end-page: 72 ident: CR9 article-title: Distribution problems in clustering publication-title: Classification and Clustering – volume: 13 start-page: 221 year: 1989 end-page: 231 ident: CR10 article-title: A simulation study of the difference Chi-square statistic for comparing latent class models under violation of regularity conditions publication-title: Appl Psychol Meas doi: 10.1177/014662168901300301 – volume: 133 start-page: 421 year: 2006 end-page: 441 ident: CR5 article-title: The power of bootstrap and asymptotic tests publication-title: J Econom doi: 10.1016/j.jeconom.2005.06.002 – volume: 14 start-page: 359 year: 2007 end-page: 368 ident: CR6 article-title: Latent class modeling of website users’ search patterns: implications for online market segmentation publication-title: J Retail Consum Serv doi: 10.1016/j.jretconser.2007.02.007 – volume: 9 start-page: 130 issue: 1 year: 1981 end-page: 134 ident: CR25 article-title: The Bayesian bootstrap publication-title: Ann Stat doi: 10.1214/aos/1176345338 – ident: CR30 – volume: 52 start-page: 5253 issue: 12 year: 2008 end-page: 5262 ident: CR31 article-title: Maximin D-optimal designs for binary longitudinal responses publication-title: Comput Stat Data Anal doi: 10.1016/j.csda.2008.04.037 – volume: 16 start-page: 171 year: 1981 end-page: 180 ident: CR7 article-title: A Monte Carlo investigation of the likelihood ratio test for the number of components in a mixture of normal distributions publication-title: Multivar Behav Res doi: 10.1207/s15327906mbr1602_3 – volume: 115 start-page: 346 year: 2009 end-page: 350 ident: CR15 article-title: Beyond symptom dimensions: Schizophrenia risk factors for patient groups derived by latent class analysis publication-title: Schizophr Res doi: 10.1016/j.schres.2009.09.017 – year: 1968 ident: CR14 publication-title: Latent Structure Analysis – start-page: 175 year: 2004 end-page: 198 ident: CR17 article-title: Latent class models publication-title: The sage handbook of quantitative methodology for the social sciences – ident: CR35 – volume: 88 start-page: 767 year: 2001 end-page: 778 ident: CR16 article-title: Testing the number of components in a normal mixture publication-title: Biometrika doi: 10.1093/biomet/88.3.767 – year: 2000 ident: CR20 publication-title: Finite mixture models doi: 10.1002/0471721182 – volume: 8 start-page: 427 year: 2014 end-page: 442 ident: CR8 article-title: A latent class analysis of the public attitude towards the euro adoption in Poland publication-title: Adv Data Anal Classif doi: 10.1007/s11634-013-0156-0 – ident: CR21 – volume: 50 start-page: 253 year: 1985 end-page: 263 ident: CR29 article-title: On the multivariate asymptotic distribution of sequential Chi-square statistics publication-title: Psychometrika doi: 10.1007/BF02294104 – ident: CR19 – volume: 24 start-page: 492 year: 1996 end-page: 616 ident: CR13 article-title: Bootstrapping goodness-of-fit measures in categorical data analysis publication-title: Sociol Methods Res doi: 10.1177/0049124196024004004 – volume: 5 start-page: 329 year: 1970 end-page: 350 ident: CR37 article-title: Pattern clustering by multivariate mixture analysis publication-title: Multivar Behav Res doi: 10.1207/s15327906mbr0503_6 – year: 1988 ident: CR3 publication-title: Statistical power analysis for the behavioral sciences – volume: 27 start-page: 143 year: 2010 end-page: 170 ident: CR12 article-title: On the use of non-local prior densities in Bayesian hypothesis tests publication-title: J R Stat Soc doi: 10.1111/j.1467-9868.2009.00730.x – volume: 23 start-page: 6 year: 1996 end-page: 28 ident: CR2 article-title: Probabilistic models in cluster analysis publication-title: Comput Stat Data Anal doi: 10.1016/0167-9473(96)88919-5 – volume: 25 start-page: 369 year: 1993 end-page: 379 ident: CR38 article-title: Inferring market structure with aggregate data: a latent segment logit approach publication-title: J Mark Res doi: 10.2307/3172888 – volume: 56 start-page: 271 year: 2003 end-page: 288 ident: CR32 article-title: Type I errors and power of the parametric bootstrap goodness-of-fit test: full and limited information publication-title: Br J Math Stat Psychol doi: 10.1348/000711003770480048 – ident: CR36 – volume: 36 start-page: 318 year: 1987 end-page: 324 ident: CR18 article-title: On bootstrapping the likelihood ratio test statistic for the number of components in a normal mixture publication-title: Appl Stat J R Stat Soc – volume: 14 start-page: 535 year: 2007 end-page: 569 ident: CR22 article-title: Deciding on the number of classes in latent class analysis and growth mixture modeling: a monte carlo simulation study publication-title: Struct Equ Model doi: 10.1080/10705510701575396 – volume: 6 start-page: 461 year: 1978 end-page: 464 ident: CR26 article-title: Estimating the dimension of a model publication-title: Ann Stat doi: 10.1214/aos/1176344136 – volume: 14 start-page: 359 year: 2007 ident: 251_CR6 publication-title: J Retail Consum Serv doi: 10.1016/j.jretconser.2007.02.007 – volume: 18 start-page: 450 year: 2010 ident: 251_CR34 publication-title: Political Anal doi: 10.1093/pan/mpq025 – ident: 251_CR36 – volume: 90 start-page: 991 year: 2003 ident: 251_CR11 publication-title: Biometrika doi: 10.1093/biomet/90.4.991 – volume: 23 start-page: 6 year: 1996 ident: 251_CR2 publication-title: Comput Stat Data Anal – year: 2015 ident: 251_CR23 publication-title: Adv Data Anal Classif – volume: 13 start-page: 221 year: 1989 ident: 251_CR10 publication-title: Appl Psychol Meas doi: 10.1177/014662168901300301 – ident: 251_CR19 – volume: 24 start-page: 492 year: 1996 ident: 251_CR13 publication-title: Sociol Methods Res doi: 10.1177/0049124196024004004 – volume: 72 start-page: 133 year: 1985 ident: 251_CR28 publication-title: Biometrika doi: 10.1093/biomet/72.1.133 – volume: 9 start-page: 130 issue: 1 year: 1981 ident: 251_CR25 publication-title: Ann Stat doi: 10.1214/aos/1176345338 – volume: 52 start-page: 5253 issue: 12 year: 2008 ident: 251_CR31 publication-title: Comput Stat Data Anal doi: 10.1016/j.csda.2008.04.037 – volume: 16 start-page: 171 year: 1981 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| Title | Power analysis for the bootstrap likelihood ratio test for the number of classes in latent class models |
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