Scientific Software International Inc. is acquired by Vector Psychometric Group.
We are happy to announce that in early 2020, Scientific Software International Inc., became a wholly owned subsidiary of Vector Psychometric Group, LLC, a North Carolina-based software and consulting company. We believe this exciting new development in SSI’s corporate history will reinvigorate the SSI products that have for so long formed the backbone of research in a variety of fields.
An important part of this evolution of SSI is the gradual roll-out of a new software delivery and support model for all our programs. We call it SSI Live™.
HLM is the first program to transition. After purchasing an SSI Live™ Standard subscription, you will be entitled to:
1) download multiple installs (not possible previously unless with purchasing a special license),
2) free access to all upgrades or updates during the period where the subscription is active,
3) free software support, and
4) discounts on subscriptions to other SSI programs.
Additional educator benefits are included. Visit SSI Live™ for more information.
The HLM8 program has a number of new statistical features.
Estimating HLM from incomplete data
In HLM 8, the ability to estimate an HLM from incomplete data was added. This is a completely automated approach that generates and analyses multiply imputed data sets from incomplete data. The model is fully multivariate and enables the analyst to strengthen imputation through auxiliary variables. This means that the user specifies the HLM; the program automatically searches the data to discover which variables have missing values and then estimates a multivariate hierarchical linear model (”imputation model”) in which all variables having missed values are regressed on all variables having complete data. The program then uses the resulting parameter estimates to generate M imputed data sets, each of which is then analysed in turn. Results are combined using the “Rubin rules”.
Flexible Combinations of Fixed Intercepts and Random Coefficients
Another new feature of HLM 8 is that flexible combinations of Fixed Intercepts and Random Coefficients (FIRC) are now included in HLM2, HLM3, HLM4, HCM2, HCM3 and HLM2.
A concern that can arise in multilevel causal studies is that random effects may be correlated with treatment assignment. For example, suppose that treatments are assigned non-randomly to students who are nested within schools. Estimating a two-level model with random school intercepts will generate bias if the random intercepts are correlated with treatment effects. The conventional strategy is to specify a fixed effects model for schools. However, this approach assumes homogeneous treatment effects, possibly leading to biased estimates of the average treatment effect, incorrect standard errors, and inappropriate interpretation. HLM 8 allows the analyst to combine fixed intercepts with random coefficients in models that address these problems and to facilitate a richer summary including an estimate of the variation of treatment effects and empirical Bayes estimates of unit-specific treatment effects. This approach was proposed in Bloom, Raudenbush, Weiss and Porter (2017).