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Binary models 2

Binary models 2. LCGA model of frequent bedwetting + tests of gender invariance. Latent Class Growth Analysis. Alternative to LLCA More parsimonius than LLCA Unlikely to capture some shapes e.g. relapse

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Binary models 2

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  1. Binary models 2 LCGA model of frequent bedwetting + tests of gender invariance

  2. Latent Class Growth Analysis • Alternative to LLCA • More parsimonius than LLCA • Unlikely to capture some shapes e.g. relapse • Fits polynomials on logit scale, not in probability space (more flexible than one might think)

  3. The data – frequent wetting

  4. The plan • Fit LLCA and LCGA models of the following: • model frequent bedwetting on boys and girls separately • Combine dataset and fit variant model with KNOWNCLASS • Test for gender invariance by constraining parameters across gender groups

  5. Sex specific models

  6. LLCA results

  7. Fitting LCGA model variable: <snip> classes = c (3) ; useobservations (sex == 1); analysis: <snip> model: %OVERALL% I S Q | nwet_1@0 nwet_2@1 nwet_3@2 nwet_4@3 nwet_5@5;

  8. Sex specific models

  9. LCGA / LLCA comparison LLCA LCGA Shapes v similar Parameters: LLCA (17) versus LCGA (11) LCGA BICs lower than LLCA

  10. Fitting LCGA KNOWNCLASS model variable: <snip> classes = sex (2) c (3) ; knownclass = sex (kz021 = 1 kz021 = 2); analysis: <snip> model: %OVERALL% I S Q | nwet_1@0 nwet_2@1 nwet_3@2 nwet_4@3 nwet_5@5;

  11. LCGA knownclass results

  12. LCGA Invariant model model: %OVERALL% I S Q | nwet_1@0 nwet_2@1 nwet_3@2 nwet_4@3 nwet_5@5; c on sex; %sex#1.c#1% %sex#2.c#1% [i] (1); [i] (1); [s] (11); [s] (11); [q] (111); [q] (111); %sex#1.c#2% %sex#2.c#2% [i] (2); [i] (2); [s] (22); [s] (22); [q] (222); [q] (222); %sex#1.c#3% %sex#2.c#3% [i] (3); [i] (3); [s] (33); [s] (33); [q] (333); [q] (333);

  13. LCGA knownclass results

  14. LCGA knownclass Invariant

  15. LLCA knownclass Invariant %sex#1.c#2% [NWET_KK4$1] (11); [NWET_KM4$1] (12); [NWET_KP4$1] (13); [NWET_KR4$1] (14); [NWET_KU4$1] (15); %sex#2.c#2% [NWET_KK4$1] (11); [NWET_KM4$1] (12); [NWET_KP4$1] (13); [NWET_KR4$1] (14); [NWET_KU4$1] (15); %sex#1.c#3% [NWET_KK4$1] (21); [NWET_KM4$1] (22); [NWET_KP4$1] (23); [NWET_KR4$1] (24); [NWET_KU4$1] (25); %sex#2.c#3% [NWET_KK4$1] (21); [NWET_KM4$1] (22); [NWET_KP4$1] (23); [NWET_KR4$1] (24); [NWET_KU4$1] (25); %OVERALL% c on sex; %sex#1.c#1% [NWET_KK4$1] (1); [NWET_KM4$1] (2); [NWET_KP4$1] (3); [NWET_KR4$1] (4); [NWET_KU4$1] (5); %sex#2.c#1% [NWET_KK4$1] (1); [NWET_KM4$1] (2); [NWET_KP4$1] (3); [NWET_KR4$1] (4); [NWET_KU4$1] (5);

  16. LCGA/LLCA Invariant results

  17. Summary • LCGA is a possible, more parsimonius alternative, to LLCA when trajectory shapes are well-behaved • One should approach an invariant model via individual models before combining data within a parameter variant knownclass model

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