Markov Chain Monte Carlo method for generating posterior draws of the parameters of the unrestricted general location model, given a matrix of incomplete mixed data. At each step, missing data are randomly imputed under the current parameter, and a new parameter value is drawn from its posterior distribution given the completed data. After a suitable number of steps are taken, the resulting value of the parameter may be regarded as a random draw from its observed-data posterior distribution. May be used together with imp.mix to create multiple imputations of the missing data.
● Data Source:
CranContrib
● Keywords: models
● Alias: da.mix
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Computes maximum-likelihood estimates for the parameters of the unrestricted general location model from an incomplete mixed dataset.
● Data Source:
CranContrib
● Keywords: models
● Alias: em.mix
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Initialize random number generator seed for mix package.
● Data Source:
CranContrib
● Keywords: models
● Alias: rngseed
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This function, when used with da.mix or dabipf.mix, can be used to create proper multiple imputations of missing data under the general location model with or without restrictions.
● Data Source:
CranContrib
● Keywords: models
● Alias: imp.mix
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Present parameters of general location model in an understandable format.
● Data Source:
CranContrib
● Keywords: models
● Alias: getparam.mix
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Combines estimates and standard errors from m complete-data analyses performed on m imputed datasets to produce a single inference. Uses the technique described by Rubin (1987) for multiple imputation inference for a scalar estimand.
● Data Source:
CranContrib
● Keywords: models
● Alias: mi.inference
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Markov Chain Monte Carlo method for generating posterior draws of the parameters of the unrestricted general location model, given a matrix of incomplete mixed data. After a suitable number of steps are taken, the resulting value of the parameter may be regarded as a random draw from its observed-data posterior distribution. May be used together with imp.mix to create multiple imputations of the missing data.
● Data Source:
CranContrib
● Keywords: models
● Alias: dabipf.mix
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This function performs grouping and sorting operations on a mixed dataset with missing values. It creates a list that is needed for input to em.mix, da.mix, imp.mix, etc.
● Data Source:
CranContrib
● Keywords: models
● Alias: prelim.mix
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Computes maximum-likelihood estimates for the parameters of the general location model from an incomplete mixed dataset.
● Data Source:
CranContrib
● Keywords: models
● Alias: ecm.mix
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Calculates the observed-data loglikelihood under the general location model at a user-specified parameter value.
● Data Source:
CranContrib
● Keywords: models
● Alias: loglik.mix
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providing 
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