Pages that link to "Item:Q5739291"
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The following pages link to Marginal regression models for clustered count data based on zero‐inflated Conway–Maxwell–Poisson distribution with applications (Q5739291):
Displaying 16 items.
- A flexible zero-inflated model to address data dispersion (Q86477) (← links)
- Analysis of zero-inflated clustered count data: a marginalized model approach (Q452693) (← links)
- A simple and useful regression model for fitting count data (Q2084721) (← links)
- A new long-term survival model with dispersion induced by discrete frailty (Q2308433) (← links)
- Underdispersion models: Models that are “under the radar” (Q4606452) (← links)
- Analyzing clustered count data with a cluster-specific random effect zero-inflated Conway–Maxwell–Poisson distribution (Q5035761) (← links)
- A multilevel zero-inflated Conway–Maxwell type negative binomial model for analysing clustered count data (Q5065301) (← links)
- A flexible regression model for zero- and <i>k</i>-inflated count data (Q5065306) (← links)
- Likelihood-based tests in zero-inflated power series models (Q5107333) (← links)
- GEE-based zero-inflated generalized Poisson model for clustered over or under-dispersed count data (Q5107485) (← links)
- Zero‐inflated Poisson model with clustered regression coefficients: Application to heterogeneity learning of field goal attempts of professional basketball players (Q6059436) (← links)
- Analyzing longitudinal clustered count data with zero inflation: Marginal modeling using the Conway–Maxwell–Poisson distribution (Q6071003) (← links)
- Conway-Maxwell-Poisson regression models for dispersed count data (Q6602132) (← links)
- A longitudinal Bayesian mixed effects model with hurdle Conway-Maxwell-Poisson distribution (Q6627663) (← links)
- Analyzing dental fluorosis data using a novel Bayesian model for clustered longitudinal ordinal outcomes with an inflated category (Q6629962) (← links)
- Poisson-Birnbaum-Saunders regression model for clustered count data (Q6665516) (← links)
