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Variance Reduction
The Monte Carlo methods described in the previous chapters are subject to variation due to the randomness inherent in sample generation. Ideally we...
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Variance Control Procedures
This chapter covers the concepts of variance and sources of variation for clinical trial data. Common metrics to quantify the extent of variability...
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Factorial Analysis of Variance (ANOVA)
Many empirical studies involve two or more independent variables. Analysis of variance (ANOVA) can easily be extended to these situations, and in...
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The estimated causal effect on the variance based on the front-door criterion in Gaussian linear structural equation models: an unbiased estimator with the exact variance
In this paper, we assume that cause–effect relationships between random variables can be represented by a Gaussian linear structural equation model...
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Variance estimation for average treatment effects estimated by g-computation
The average treatment effect is used to evaluate effects of interventions in a population. Under certain causal assumptions, such an effect may be...
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Mean and Variance for Count Regression Models Based on Reparameterized Distributions
We introduce a new regression model for count data where the response variable is mainly in the class of inflated-parameter generalized power series...
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One-Way Analysis of Variance (ANOVA)
The methods introduced so far test difference hypotheses for a maximum of two groups or conditions with a t-test. Many research designs will actually...
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Variance matrix estimation in multivariate classical measurement error models
Measurement errors are often encountered in several continuous variables in a data set, and various methods have been proposed to handle these...
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Change point in variance of fractionally integrated noise
This paper studies the quasi-maximum likelihood estimator (quasi-MLE) of a change point in variance for the fractionally integrated noise with memory...
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Repeated-Measures Analysis of Variance (ANOVA)
Just as the one-way (i.e., single-factor) analysis of variance (ANOVA) was a generalization of the t-test for independent samples, the...
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A Variance-Based Sensitivity Analysis Approach for Identifying Interactive Exposures
Chemical mixtures can significantly affect human health, but understanding the interactions among various chemical exposures and identifying...
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Variance Components and Precision
Often the precision of performance is as important as accuracy. Methods for estimating measures of precision are described, along with associated...
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The distribution of the sample correlation coefficient under variance-truncated normality
The non-null distribution of the sample correlation coefficient under bivariate normality is derived when each of the associated two sample variances...
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Introducing a Family of Distributions by Using the Class of Normal Mean–Variance Mixture
In this study, we present a new family of asymmetric distributions by taking into consideration the multivariate normal mean–variance (NMV) mixture...
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A Monte Carlo permutation procedure for testing variance components in generalized linear regression models
Testing zero variance components is of utmost importance in various applications empowered by the use of mixed-effects models. Focusing on...
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DDCAL: Evenly Distributing Data into Low Variance Clusters Based on Iterative Feature Scaling
This work studies the problem of clustering one-dimensional data points such that they are evenly distributed over a given number of low variance...
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Generalized Bayes Minimax Estimators of the Variance of a Multivariate Normal Distribution
The problem of estimating the variance of a multivariate normal distribution is considered under quadratic loss. A large class of generalized Bayes...
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Frequentist Conditional Variance for Nonlinear Mixed-Effects Models
Nonlinear mixed-effects models are commonly used in fisheries and ecological studies to account for complex relationships and dependencies in data....
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Inference Using Analysis of Variance (ANOVA) for Comparing Multiple Means
This chapter discusses single-factor analysis of variance (ANOVA), which is mainly applied to compare three or more independent means. The term...
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Robust Response Transformations for Generalized Additive Models via Additivity and Variance Stabilization
The AVAS (Additivity And Variance Stabilization) algorithm of Tibshirani provides a non-parametric transformation of the response in a linear model...