Sentence examples for model for imputation from inspiring English sources

The method of chained equations recognizes that in many instances, it might be better to engage in a series of single univariate imputations along with diagnostic checking rather than a omnibus multivariate model for imputation that might be sensitive to specification issues.

First, we want to select a particular model for imputation.

They decide to use multiple imputation, where the model for imputation assumes lumbar muscle strength is normally distributed with different means but equal variances in the two treatment groups.

Returning to the missing data example above, if Zheng et al. were to use single (as opposed to multiple) imputation as a sensitivity analysis, as suggested in [ 5], this could well lead to different conclusions, despite our criticism above that the model for imputation is identical to the model for the primary analysis.

To handle missing data, we implemented multiple imputation by chained equations using classification and regression trees (MICE-CART) as the conditional models for imputation [ 26].

It does not underestimate variability, and the models for imputation and efficacy analysis can be developed independently, thereby increasing the realism of the assumptions underlying the imputation [ 2].

Reports of conditions other than anxiety and depression and in non-random-digit-dialling surveys may not be amenable to this non-response modelling for imputation.

We can noticed the work of Bar-Joseph et al. who described a model-based spline fitting method for time-series data [ 31] and Schliep et al. who used hidden Markov models for imputation [ 32].

eOne article [ 91] stated that MI was used on the basis of either propensity scoring or regression modelling for imputation of missing data in the primary and secondary outcome measures.

Table 1 Imputation models for different types of variables Type of variable The model used for imputation Continuous variable Linear regression Binary variable Logistic regression Ordinal variable Ordinal logistic regression Nominal variable Multinomial logistic regression.

The regression model used for imputation included variables for gestational age, SGA or non-SGA, birth order, maternal age, marital status, and Apgar score 5-minutes after birth [ 26].