Types Of Research Studies
Types of Research Studies
Research studies take three basic forms:
Descriptive studies are designed primarily to describe what is going on or what exists. Public opinion polls that seek only to describe the proportion of people who hold various opinions are primarily descriptive in nature. For instance, if you want to know what percent of the population would vote for a Democrat or a Republican in the next presidential election, you are simply interested in describing something.
Relational studies look at the relationships between or among two or more variables. A public opinion poll that compares what proportion of males and females say they would vote for a Democratic or a Republican candidate in the next presidential election is essentially studying the relationship between gender and voting preference.
Causal studies are designed to determine whether one or more variables (e.g., a program or a treatment variable) cause or affect one or more outcome variables. If you performed a public opinion poll to try to determine if a recent political advertising campaign changed voter preferences, you would essentially be studying whether the campaign (cause) changed the proportion of voters who would vote Democratic or Republican (effect).
The three study types can be viewed as cumulative, that is, a relational study assumes that you can first describe by measuring or observing each of the variables you are trying to relate. A causal study assumes that you can describe both the cause and the effect variables and that you can show that they are related. Causal studies are probably the most demanding of the three types of studies to perform.
Time is an important element of any research design. One of the most fundamental distinctions in research design nomenclature is the cross-sectional versus the longitudinal study. A cross-sectional study is one that takes place at a single point in time. In effect, the researcher is taking a slice, or a cross section, of whatever it is that is being observed or measured. A longitudinal study is one that takes place over time, and there are at least two (and often more) waves of measurement in a longitudinal design.
A further distinction is made between two types of longitudinal designs: repeated measures and time series. There is no universally agreed upon rule for distinguishing between these two terms, but in general, if you have two or a few waves of measurement, you are using a repeated measures design. If you have many waves of measurement over time, you have a time series. How many is many? Usually, the term time series implies at least 20 waves of measurement, and often far more. Sometimes, the way in which one distinguishes between these longitudinal designs is through the analysis methods being employed. Time series analysis requires at least 20 or so observations over time. Repeated measures analyses are not often used with as many as 20 waves of measurement.