SOLAS for Missing Data Analysis
Pharmaceutical Clinical Trials
Missing values are inevitable in most clinical trial studies. Using SOLAS to impute missing values in primary endpoint data reduces potential bias, while increasing the accuracy of subsequent analysis. Incorporating SOLAS into your clinical trial protocol, also helps you comply with FDA & EMA guidelines on missing data & sensitivity analysis.
Market Research Surveys
The Hot Deck/Nearest Neighbor method in SOLAS allows market researchers to intuitively & scientifically impute missing survey data. SOLAS guides you through the hot-decking process, so that you understand how the completed dataset is compiled, allowing you to explain the survey results with confidence to colleagues & clients.
Academic Research Projects
Academic researchers will love the new collapse missing data pattern feature. This unique visualisation tool allows you to quickly & simply interpret missing values in your data. Academic organizations can also benefit from reduced researcher pricing and special offer student discounts
Government & Population Studies
The new 64-Bit capability boosts SOLAS’s processing powering and allows government agencies to impute missing values in much larger datasets. In addition, the Predictive Mean Matching multiple imputation method in SOLAS (as described by Roderick J. Little 1988) works well with very large survey and population studies data.
SOLAS for Missing Data Analysis was developed with guidance from Donald B. Rubin, the inventor of Multiple Imputation.
SOLAS 4.0 offers 5 different methods for multiple imputation in addition to 4 single imputation techniques. You choose the most appropriate method for your particular data set.
Amazing new graphics in SOLAS 4.0 allow you to visualize your missing data issues like never before.
SOLAS can be purchased as an ANNUAL type of license for commercial, government and student uses.
Academic Users can purchase PERPETUAL licenses for discounted prices
© 2012 Statistical Solutions. All rights reserved.