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We then further extended the method of Efron by developing a multivariate model able to handle replicate experiments.
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We are currently developing a multivariate version of the approach that is less ad hoc in improving power, by using multiple predictors at the last-stage regression.
We test this hypothesis by developing a combination of multivariate logistic, Poisson and beta regression techniques using Latin American Migration Project data to determine how agricultural land use change compared among migrant and non-migrant households in Costa Rica, El Salvador, Guatemala, and Nicaragua.
Cox proportional hazards regression analysis was used to develop a multivariate model of prognostic factors by considering the factors that were associated with survival.
Ahmadzadeh et al. (2013) developed a multivariate exponentially weighted moving average (MEWMA) control chart by using neural network for identifying the step change point as well diagnosing the variable responsible of the change in the multivariate process mean vector.
In this paper, we develop a multivariate Gaussian conditional autoregressive model for use on mismatched lattices.
We developed a multivariate curve resolution model that enabled quantitative biochemical analysis of the TE constructs.
We developed a multivariate Cox proportional hazards model for re-incarceration including health-related covariates from a pre-release survey.
We developed a multivariate linear regression model to identify any relationship to social media influence, measured by the PageRank.
Variables with a significant P-value were then used to develop a multivariate Cox model.
This study applies a STAR modeling approach to develop a multivariate explanatory model for cholera.
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