Last data update: 2014.03.03

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Results 1 - 10 of 10 found.
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cluster.im.ivreg (Package: clusterSEs) : Cluster-Adjusted Confidence Intervals And p-Values For GLM

Computes p-values and confidence intervals for GLM models based on cluster-specific model estimation (Ibragimov and Muller 2010). A separate model is estimated in each cluster, and then p-values and confidence intervals are computed based on a t/normal distribution of the cluster-specific estimates.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.im.ivreg
● 0 images

cluster.bs.ivreg (Package: clusterSEs) : Pairs Cluster Bootstrapped p-Values For Regression With Instrumental Variables

This software estimates p-values using pairs cluster bootstrapped t-statistics for instrumental variables regression models (Cameron, Gelbach, and Miller 2008). The data set is repeatedly re-sampled by cluster, a model is estimated, and inference is based on the sampling distribution of the pivotal (t) statistic.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.bs.ivreg
● 0 images

cluster.bs.mlogit (Package: clusterSEs) : Pairs Cluster Bootstrapped p-Values For mlogit

This software estimates p-values using pairs cluster bootstrapped t-statistics for multinomial logit models (Cameron, Gelbach, and Miller 2008). The data set is repeatedly re-sampled by cluster, a model is estimated, and inference is based on the sampling distribution of the pivotal (t) statistic.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.bs.mlogit
● 0 images

cluster.bs.plm (Package: clusterSEs) : Pairs Cluster Bootstrapped p-Values For PLM

This software estimates p-values using pairs cluster bootstrapped t-statistics for fixed effects panel linear models (Cameron, Gelbach, and Miller 2008). The data set is repeatedly re-sampled by cluster, a model is estimated, and inference is based on the sampling distribution of the pivotal (t) statistic.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.bs.plm
● 0 images

cluster.wild.ivreg (Package: clusterSEs) : Wild Cluster Bootstrapped p-Values For For Regression With Instrumental Variables

This software estimates p-values using wild cluster bootstrapped t-statistics for instrumental variables regression models (Cameron, Gelbach, and Miller 2008). Residuals are repeatedly re-sampled by cluster to form a pseudo-dependent variable, a model is estimated for each re-sampled data set, and inference is based on the sampling distribution of the pivotal (t) statistic. Users may choose whether to impose the null hypothesis for independent variables; the null is never imposed for the intercept or any model that includes factor variables. Confidence intervals are only reported when the null hypothesis is not imposed.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.wild.ivreg
● 0 images

cluster.im.glm (Package: clusterSEs) : Cluster-Adjusted Confidence Intervals And p-Values For GLM

Computes p-values and confidence intervals for GLM models based on cluster-specific model estimation (Ibragimov and Muller 2010). A separate model is estimated in each cluster, and then p-values and confidence intervals are computed based on a t/normal distribution of the cluster-specific estimates.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.im.glm
● 0 images

cluster.bs.glm (Package: clusterSEs) : Pairs Cluster Bootstrapped p-Values For GLM

This software estimates p-values using pairs cluster bootstrapped t-statistics for GLM models (Cameron, Gelbach, and Miller 2008). The data set is repeatedly re-sampled by cluster, a model is estimated, and inference is based on the sampling distribution of the pivotal (t) statistic.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.bs.glm
● 0 images

cluster.wild.glm (Package: clusterSEs) : Wild Cluster Bootstrapped p-Values For Linear Family GLM

This software estimates p-values using wild cluster bootstrapped t-statistics for linear family GLM models (Cameron, Gelbach, and Miller 2008). Residuals are repeatedly re-sampled by cluster to form a pseudo-dependent variable, a model is estimated for each re-sampled data set, and inference is based on the sampling distribution of the pivotal (t) statistic. Users may choose whether to impose the null hypothesis for independent variables; the null is never imposed for the intercept or any model that includes factor variables. Confidence intervals are only reported when the null hypothesis is not imposed.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.wild.glm
● 0 images

cluster.im.mlogit (Package: clusterSEs) : Cluster-Adjusted Confidence Intervals And p-Values For mlogit

Computes p-values and confidence intervals for multinomial logit models based on cluster-specific model estimation (Ibragimov and Muller 2010). A separate model is estimated in each cluster, and then p-values and confidence intervals are computed based on a t/normal distribution of the cluster-specific estimates.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.im.mlogit
● 0 images

cluster.wild.plm (Package: clusterSEs) : Wild Cluster Bootstrapped p-Values For PLM

This software estimates p-values using wild cluster bootstrapped t-statistics for fixed effects panel linear models (Cameron, Gelbach, and Miller 2008). Residuals are repeatedly re-sampled by cluster to form a pseudo-dependent variable, a model is estimated for each re-sampled data set, and inference is based on the sampling distribution of the pivotal (t) statistic. The null is never imposed for PLM models.
● Data Source: CranContrib
● Keywords:
● Alias: cluster.wild.plm
● 0 images