Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 20 for “"Zero Inflation"”.
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Investigating the Effects of Ethnic/Racial Identity on ADHD and Comorbid Psychopathology
… mixed-effects negative binomial regression with zero inflation to investigate the interactive effects between ADHD symptoms and three ERI dimensions on depressive symptoms and weekly alcohol consumption. The conditional model yielded a significant moderating effect of ERI affirmation on the …
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Model-based clustering for multivariate time series of counts
… framework for univariate and multivariate zero-inflated time series of counts and applies the models in a clustering scheme to identify groups of count series with similar behavior. The basic modeling framework used is observation-driven Poisson regression with generalized linear model …
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Poisson regression models for interval censored count data.
… censored Poisson counts in the presence of zero inflation and missing data. As a motivating example, we consider data arising from a Human Immunodeficiency Virus (HIV) vaccine trial featuring imprecise counts, missing data, and an abundance of values which are either exactly observed to be …
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New Multivariate Zero-Inflated Beta-Binomial Distribution
The multivariate zero-inflated beta-binomial model is significantly important for modelling and analyzing multivariate proportional data with extra zeros. Comparing with the binomial model, the beta-binomial model is a better alternative for explicitly accounting for over-dispersion, and …
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A GLMM analysis of data from the Sinovuyo Caring Families Program (SCFP)
… These summed scores were often right skewed with zero-inflation. All the effects (fixed and random) were estimated through the method of maximum likelihood. Primarily, an intention-to-treat analysis was done after which a per-protocol analysis was also implemented with participants who attended a …
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Semiparametric Bayesian Count Data Models
… caused by missing covariates, and/or excess of zero observations in our data. Both distributional issues results in deviations of the response distribution from the classical Poisson assumption. We may in addition want to extend our predictor to model temporal or spatial correlation and possibly …
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Variable Selection and Hypothesis Testing for High-Dimensional Models in Mental Health Research
… structures, and outcomes exhibiting excess zeros. These characteristics pose significant challenges for variable selection, model estimation, hypothesis testing, and sample size determination, often undermining statistical stability, interpretability, and computational efficiency. This …
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Bayesian modelling of mixed outcome types using random effect.
… response, a misclassified covariate, and a zero-inflated discrete response. Simulation studies indicate that our models provide good estimates of regression coefficients, response variability, and the correlation between responses. We also show that ignoring the random effects leads to a …
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Extended Poisson Models for Count Data With Inflated Frequencies
<p>Count data often exhibits inflated counts for zero. There are numerous papers in the literature that show how to fit Poisson regression models that account for the zero inflation. However, in many situations the frequencies of zero and of some other value <em>k</em> tends to be higher than the …
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Geostatistical methods for disease prevalence mapping
… data and modelling of spatially structured zero-inflation. We then describe three applications that have arisen through our collaborations with researchers and public health programmers in African countries.
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Causal Inference Methods for Microbiome Data
… mediation. By integrating mixed-effects zero-inflated generalized linear models (MEZIGLM) with natural effects models, this method accounts for overdispersion, zero inflation, and subject-level heterogeneity while constructing generalized confidence intervals for natural direct and …
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Bayesian approach for modeling zero-inflated plant percent covers using spatial left-censored beta regression
… with ecological data is the large number of zeros: most of the time species are not observed at the sampling location. Zeros can be thought to arise from ecological reasons or due to randomness. This problem of zero inflation is well studied for discrete positive data, such as counts and …
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Modified mean and quantile regression models for citation analysis
… This problem might be remedied by fitting a zero-modified, i.e. zero-inflated or a zero-deflated, distribution that allows the predicted number of zeros to more closely approximate the number of zeros in a dataset. Whilst previous scientometric studies have fitted zero-inflated distributions …
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Geostatistical modelling of recreational fishing data: A fine-scale spatial analysis
… recreational fishing data are highly skewed, zero-inflated and when expressed as ratios are impacted by the small number problem, which can influence estimates obtained from the traditional kriging. In addition, the use of recreational fishing data obtained through surveys may influence …
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A Citizen-Science Approach for Urban Flood Risk Analysis Using Data Science and Machine Learning
… (LASSO) regression analysis, with an embedded Zero-Inflation (ZI) model, the variables statistically significant as predictors, specific to each zip code, are detected. Second, with an intent to understand how factors affect the spatial variability of street flooding, the Random Forest …
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Investigaion of the Gamma Hurdle Model for a Single Population Mean
… problems is dealing with a high frequency of zeroes in a sample of data. For many distributions such as the gamma, optimal inference procedures do not allow for zeroes to be present. In practice, however, it is natural to observe real data sets where nonnegative distributions would make sense …
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Parameter Estimation for Normally Distributed Grouped Data and Clustering Single-Cell RNA Sequencing Data via the Expectation-Maximization Algorithm
… takes into account the large proportion of zeros present in the data, which can be either true biological zeros or technological noise. The assumed model for clustering is a mixture of either zero-inflated Poisson or zero-inflated negative binomial distributions, and inference is conducted …
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Bayesian approaches to problems in diagnostic testing and underreported count data.
… Finally, the last chapter extends a zero-inflated Poisson distribution accounting for underreporting into the Bayesian paradigm. We analyze this Bayesian model in multiple simulation studies. When underreporting is inaccurately estimated, model parameter estimation can be biased. …
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Joint models for nonlinear longitudinal profiles in the presence of informative censoring
… Firstly, the distribution of gametocyte data is zero-inflated with a long tail to the right. The observed longitudinal gametocyte profile also has a nonlinear relationship with time. In addition, since most malaria intervention studies are not designed to optimally measure the evolution of the …
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Copula-Based Zero-Inflated Count Time Series Models
… finance. In some cases, a specific count, say zero, may occur more often than usual. Additionally, serial dependence might be found among these counts if they are recorded over time. Overlooking the frequent occurrence of zeros and the serial dependence could lead to false inference. In this …