The research glossary defines terms used in conducting social science and policy research, for example those describing methods, measurements, statistical procedures, and other aspects of research; the child care glossary defines terms used to describe aspects of child care and early education practice and policy.
Experimental Design
A research design used to establish cause-and-effect relationships between the independent and dependent variables by means of manipulation of variables, control and randomization. A true experiment involves the random allocation of participants to experimental (treatment or intervention) and control (non-treatment or non-intervention) groups, manipulation of the independent variable (e.g., new reading or math curriculum), and the introduction of a control group for comparison purposes (e.g., classes in program that will not use new reading or math curriculum). Participants are assessed after (or before and after) the manipulation of the independent variable in order to assess its effect on the dependent variable (e.g., the reading or math skills of children in both the experimental and control groups are assessed ); differences between the groups are assumed to be due to the treatment effect.
Experimental Group
In experimental research, the group of subjects who receive the experimental treatment or intervention under investigation.
Explanatory Analysis
A method of inquiry that focuses on the formulating and testing of hypotheses. For example, instead of, or in addition to, describing Black and White differences in the reading and math skills of preschool children, the analysis focuses on testing whether factors that may contribute to these differences (e.g., resources available to children at home and in their child care programs) are in fact associated with those differences.
Exploratory Factor Analysis
A multivariate statistical method used to uncover the underlying structure (factors) of a set of variables. It is a form of factor analysis whose goal is to identify the underlying relationships between measured variables. It is especially useful when there is no hypothesis about the underlying structure of the data and the pattern of relationships between the variables. Researchers often use exploratory factor analysis to develop scales from multiple survey or assessment items. It is a way of reducing the number of items to be used in an analysis to a smaller and more meaningful set.
Exploratory Study
An exploratory study is conducted to begin to understand a research problem or question when there are few or no earlier studies and/or limited theory to refer to or rely upon to answer the question. The focus is on gaining insights and familiarity for later investigation. Many variables are often taken into account and compared, using a variety of techniques in the search for patterns.
External Validity
The degree to which the results of a study can be generalized beyond the study sample to a larger population.
Extraneous Variable
A variable that interferes with the relationship between the independent and dependent variables and which therefore needs to be controlled for in some way.
Extrapolation
Predicting the value of unknown data points by projecting beyond the range of known data points.
Face Validity
The extent to which a survey or a test appears to actually measure what the researcher claims it measures. For example, a researcher may create survey questions that s/he claims measure gender role attitudes. To have face validity, other researchers who read the survey questions must also agree that the questions do appear to measure gender role attitudes.
Factor Analysis
A form of multivariate analysis that includes a large number of variables or objects and aims to identify a smaller number of factors that are more understandable. It is a way of identifying patterns in the data and overlap in the patterns. There are two basic types: exploratory factor analysis and confirmatory factor analysis. Definitions of the two types can be found elsewhere in the glossary.