IIRDA offers professional data analysis and related services at hourly rates. There are two broad contexts for these services: Post Award and Ad Hoc. For post award services, IIRDA can be included in the proposal budget as a resource for analyzing the data resulting from the grant. In some instances, IIRDA personnel can serve as evaluators for the project. Ad hoc services involve simply contracting with IIRDA as needed for data analysis in other contexts.
In either case, services are tailored to your particular needs. A quantitative methodologist at IIRDA can analyze your data for you, with as much or as little of your participation as you desire. We are able to work with popular software packages such as SPSS, SAS, Mplus, Amos, HLM, and others.
It is important to note the ways in which professional data services differ from the free consulting available from IIRDA. Free consulting is limited in time and is in many ways aimed at helping you to help yourself. Professional data service time does not require you to be an active participant and is limited only by what you seek to pay and our availability.
|Tier One:||$35 an hour|
|Tier Two:||$67.50 an hour|
|Tier Three:||$100 an hour|
Tier One: Survey construction assistance, development of web-based surveys using Snap Surveys, and descriptive statistics
Tier Two: Multiple regression, ANOVA and related procedures, exploratory factor analysis, sampling, most power analyses
Tier Three: Structural equation modeling, multi-level modeling, Bayesian analyses, item response theory, mixture modeling, time series, models using discrete outcomes
To utilize our professional data analysis services, please contact us at firstname.lastname@example.org with a description of your data needs. We will then schedule an initial meeting to further discuss the project.
As with our free consulting services, our intention is not to accrue co-authorships. Nevertheless, academic ethics of co-authorship apply (see Responsible Conduct of Research). Should we write up results for publication, apply standard statistical techniques in a novel or creative way, or develop new techniques for your work, co-authorship may be appropriate.