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6.1: Linear growth model for a continuous outcome |
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6.2: Linear growth model for a censored outcome using a censored model |
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6.3: Linear growth model for a censored outcome using a censored-inflated model |
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6.4: Linear growth model for a categorical outcome |
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6.5: Linear growth model for a categorical outcome using the Theta parameterization |
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6.6: Linear growth model for a count outcome using a Poisson model |
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6.7: Linear growth model for a count outcome using a zero-inflated Poisson model |
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6.8: Growth model for a continuous outcome with estimated time scores |
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6.9: Quadratic growth model for a continuous outcome |
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6.10: Linear growth model for a continuous outcome with time-invariant and time-varying covariates |
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6.11: Piecewise growth model for a continuous outcome |
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6.12: Growth model with individually-varying times of observation and a random slope for time-varying covariates for a continuous outcome |
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6.13: Growth model for two parallel processes for continuous outcomes with regressions among the random effects |
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6.14: Multiple indicator linear growth model for continuous outcomes |
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6.15: Multiple indicator linear growth model for categorical outcomes |
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6.16: Two-part (semicontinuous) growth model for a continuous outcome |
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6.17: Linear growth model for a continuous outcome with first-order auto correlated residuals using non-linear constraints |
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6.18: Multiple group multiple cohort growth model |
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6.19: Discrete-time survival analysis |
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6.20: Continuous-time survival analysis using the Cox regression model |
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6.21: Continuous-time survival analysis using a parametric proportional hazards model |
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6.22: Continuous-time survival analysis using a parametric proportional hazards model with a factor influencing survival |
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