However, in some cases, analysts may need more information or statistics from the imputation process to help them with their analyses. The purpose of this paper is to demonstrate how to use SAS/STAT and SAS/IML to build model-based multiple imputation macros such that analysts can streamline ...
(1998) `Comparison of model- and multiple imputation-based approaches to longitudinal analyses with partial missingness', Struc- tural Equation, 51(1), pp. 1 - 21.Duncan TE & Duncan SC (1998) A comparison of model- and multiple imputation-based approaches to longitudinal analysis with partial...
(2005), and the idea of converting binary and ordinal longitudinal outcomes to multivariate normal outcomes in a sensible way so that re-conversion to the original scale yields the original specified marginal expectations and correlations after performing multiple imputation (Demirtas and Hedeker, 2007...
Deconvoluting cell-state abundances from bulk RNA-sequencing data can add considerable value to existing data, but achieving fine-resolution and high-accuracy deconvolution remains a challenge. Here we introduce MeDuSA, a mixed model-based method that le
propose an estimation method for the semiparametric AFTMC model based on the multiple imputation (MI) method. Both the rank estimation method (Jin et al., 2003) and the profile likelihood method (Zeng and Lin, 2007) for the semiparametric AFT model are considered in the MI approach. The pap...
We focus on performing multiple imputation by chained equations when data contain multiple incomplete multi-item scales. Recent authors have proposed imputing such data at the level of the individual item, but this can lead to infeasibly large imputation models. We use data gathered from a large ...
All these results confirm that under the normal inverse gamma prior, Bayesian imputation under normal linear model converges to the corresponding multivariate normal distribution. Conclusion Based on the theory of the non-informative margins condition proposed by Hughes et al.6, we prove the convergence...
This repository serves as a template for creating new projects based on FusionBench. It includes all the necessary configurations and boilerplate code to get started quickly. model-fusionmodel-ensemblemodel-mergingmodel-mixingfusion-bench UpdatedNov 21, 2024 ...
Returns a true or false label based on a condition you specify Boolean, Numeric, Text If(sales1>7000, 'truelabel, 'falselabel') N/A Or Returns a Boolean value of whether one of the specified values or conditions is true or not Boolean Or(fullprice, discount) fullprice || discount...
Second, machine learning models are often used in a fit-predict model, in which a model is fitted on the training set once and then reused for multiple test datasets. Transformer-based ICL algorithms, however, receive train and test data in a single pass and thus perform training and ...