Quantitative Research

Survey Research

We can accommodate requests for large or small survey projects. Whether the need is for simple or highly complex surveys, VIP Research and Evaluation has the expertise and resources to design and develop custom surveys for telephone, online, or self-administration (paper). Further, we are very adept at applying complex sampling designs and weighting formulas if necessary. See more in the Types of Research section.
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Experimental/Quasi-Experimental Design

In program evaluation, for example, it is often necessary to employ a robust research design that will accurately and effectively measure program impact. Done properly, such a project would include a comparison group, or groups, utilized to measure against the group receiving the intervention (experimental group).

Ideally, a true control group would be used as the comparison group. In this scenario, participants are randomly selected to participate in the research and then randomly assigned to either the experimental or the control group. Budgetary constraints often make utilizing a true control group unfeasible. Ethical concerns may also prohibit the use of a control group. When this is the case, quasi-control groups can be used as an alternative to a true control group. With this type of study, a second group, one that does not receive the intervention, is used as a comparison group. In this scenario, random assignment is not utilized, but instead, a comparison group is chosen and matched to the experimental group based on variables such as key demographics like age, gender, race, socio-economic status or other measures (e.g., achievement scores/measures in education).

In this example, the comparison group would be sizeable enough to make statistically-significant comparisons with the experimental group. This allows us to compare the outcome measures of two similar groups where only one has had the intervention.

Secondary Data Analysis/Inclusion

VIP Research and Evaluation sometimes uses secondary data to support research conclusions. Examples of secondary data are widely-available data, such as those from public databases, (e.g., the U.S. Census, County Health Rankings, CDC, Vital Statistics) and data collected by our clients (e.g., student attendance or performance data for a study on educational intervention). Secondary data is an important complement to primary data collection and is necessary for the full research picture.

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Through Research and Evaluation

Organizations need accurate information in order to be successful. We help our clients succeed by developing robust and efficient ways to collect the necessary information

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