Statsols Blog

An Overview of Multiple Imputation in SOLAS for Missing Data 5.0

In our previous post we discussed the pervasive problem of missing data in data analysis. To recap quickly, in a data set with 5 variables measured at the start of a study and monthly for six months, if each variable is 95% complete with a random 5% of the values missing, then the proportion of cases that are expected to be incomplete are 1-(.95)^35= 0.834. That is, only 17% of the cases would be complete and with traditional complete case analysis, you would then lose 83% of your data.

How It Works?

With Solas 5.0TM, missing values in a data set are filled-in with plausible estimates to produce a complete data set that can be analyzed using complete-data inferential methods and designed to accommodate a range of missing data scenarios in both longitudinal and single-observation study designs.

Topics: Missing Data Multiple Imputation Hot Deck Imputation

Missing Data - A Pervasive Problem in Data Analysis

Missing data are a pervasive problem in data analysis. Missing values lead to less efficient estimates because of the reduced size of the database, also standard complete-data methods of analysis no longer apply. For example, analyses such as multiple regression use only cases that have complete data, so including a variable with numerous missing values would severely reduce the sample size.

Topics: Missing Data

The DIA 2014 50th Annual Meeting

Next week from June 15-19, 2014, Statistical Solutions will be at the DIA 2014 50th Annual Meeting at the San Diego Convention Center, San Diego, CA.

 

Topics: Missing Data Industry News SOLAS for Missing Data Power & Sample Size

A Celebration of Don Rubin on His 70th Birthday

The Department of Statistics, Harvard University, Cambridge, MA will hold a celebration honouring Donald Rubin on his 70th Birthday on Saturday, March 29, 2014.

Topics: Missing Data Multiple Imputation Industry News

The Prevention and Treatment of Missing Data in Clinical Trials

The Prevention and Treatment of Missing Data in Clinical Trials Blog
November 1st – 2nd 2011, Iselin, New Jersey
by Andrew Grannell

Topics: Missing Data

PSI Expert Group on Missing Data

Brian Sullivan, Statistician and Customer Support Manager with Statistical Solutions recently contributed to the PSI Missing Data Expert Group paper that was published in the Oct-Dec issue of the Wiley-Blackwell journal Pharmaceutical Statistics. You can read the article free of charge at http://onlinelibrary.wiley.com/doi/10.1002/pst.391/pdf

Topics: Missing Data