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Thank you for your interest in the RUSH Project, which was funded by the National Institute on Disability and Rehabilitation Research (Project #H133A031402).

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Types of Logic Models

Logic models should assist projects in describing, planning, implementing, monitoring, and/or appraising a project in the most practical manner. There is no magic formula when it comes to identifying and constructing a logic model. Each project and its staff will address logic model development with different aims and approaches. The flexibility of the logic modeling process allows for a variety of perspectives and approaches to be described within the context of a project's scope of work. Following are examples of some different types of logic models that may be useful to NIDRR grantees. These are not intended to suggest a comprehensive description of all available types of logic models.

Theory Approach Logic Model

A logic model can be constructed to reflect a project's theory of how it is going to produce change within a specific target system. This is sometimes called a Theory Approach Logic Model (W. K. Kellogg Foundation, 2001). This model is based upon the theoretical premises upon which a project was designed and provides a theory-based rationale for the exploration, problems, issues, needs to be pursued by the project, and how the project intends to produce "solutions" connecting project results with proven strategies. The rationale should explain why a project design is likely to be successful.

Theory Approach Logic Models are often found in grant proposals because they make a case for how the elements of the project design fit together to produce desired outcomes. These logic models emphasize the problem or concern addressed by the project design and the theory-based principles upon which activities are developed and results are expected. Emphasis in a Theory Approach Logic Model is often placed on the following elements:

Outcomes Approach Logic Model

This model emphasizes the rationale between the project's activities and the expected or targeted outcomes. An outcomes-oriented logic model describes the linkage between planned activities and their expected outcomes. An activity or set of related activities is projected to cause an outcome or set of outcomes to occur in this type of modeling.

The Outcomes Approach Logic Model is highly descriptive of specific activities and expected outcomes and would tend to emphasize the following elements:

Activities Approach Logic Model

This model emphasizes how the project's activities stem from the available resources and are linked to the expected outcomes. Emphasis in this type of model is placed on the activities, which are usually described in fine detail. Activities describe the scope-of-work of the project and are often placed in time to indicate when certain activities will begin and end. This type of model can be used as a management tool to assess activity initiation, culmination, and demonstration of expected results.

        An Activities Approach Logic Model often emphasizes the following elements:

Research Performance Logic Models

Logic models are not always linear in construction, with one element leading directly to the next. They are flexible enough not to require such a relationship among their elements. For example, research-oriented projects often are best described in a recurring "loop" between the project's input and activities, its research design and implementation, and its results or output. Related research is often required to produce sufficient confidence or rigor to be used by others key audiences or systems to produce change or other effects. This suggests that the output of one research activity constitutes the input for another research activity and so on – until reliable results are produced. In a logic model, this could look like:

Input → Research Activities → Output → Outcomes ,(back to Inputs to repeate)

Generally speaking, no single research activity and accompanying result is sufficient to expect widespread implementation and short- and mid-term outcomes, and long-range impact. Rather, research is characterized as an iterative process where the results of research are subject to review, analysis, and replication before they may be fully accepted by the scientific community as sufficient to base decisions upon in the real world. To be most useful, logic models need to reflect this reality in the production of research-based findings that can be widely used.


W. K. Kellogg Foundation. (2001). Using logic models to bring together planning, evaluation, & action: Logic model development guide. Battle Creek, MI: Author. Retrieved August 2, 2004:

NIDRR Project Number: H133A031402
Last Updated: Wednesday, 07 October 2009 at 01:41 PM.

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