Descriptive research describes something as it naturally occurs. Because researchers do not manipulate any variables, descriptive research cannot be used to characterize “cause-and-effect” relationships.
In contrast, experimental research involves manipulating an independent variable to see how it impacts a dependent variable. Experimental research can be used to investigate “why” questions and establish cause-and-effect relationships.
Continue reading: What is the difference between descriptive and experimental research?
Longitudinal studies are broadly categorized as prospective (researchers recruit participants and collect their data over the following years) or retrospective (researchers use an existing longitudinal dataset to “look back in time” at factors contributing to an outcome of interest).
Specific longitudinal study designs include the following.
- Repeated cross-sectional study: Researchers collect the same data from distinct samples of the same population over time (essentially a cross-sectional study that is repeated with different people).
- Cohort study: Participants who share one or more characteristics (or “exposures”) are followed over time to observe which outcomes they develop.
- Panel study: A group of participants, often randomly selected, is studied over time to observe changes in their attitudes or behaviors.
Continue reading: What are the types of longitudinal studies?
There is no minimum duration for longitudinal studies. Some are only a few days or weeks long, but many last for years or even decades.
The only requirement for a study to be considered longitudinal is that data are collected repeatedly from participants.
Continue reading: How long is a longitudinal study?
In a repeated cross-sectional study, the same population is studied at multiple time points. At each time point, data are collected from a different sample of the population.
A repeated cross-sectional study is a type of longitudinal study because data are collected repeatedly over a period of time.
However, as the name suggests, it also resembles a cross-sectional study. Data are obtained from each group of participants at a single time point, and this process is repeated several times.
Repeated cross-sectional studies are helpful for studying changes in a population over time.
Continue reading: What is a repeated cross-sectional study?
In a cross-sectional study, researchers recruit a group of participants (often using random sampling), then measure exposure variables (e.g., risk factors—such as smoking) and outcomes (e.g., lung cancer). Cross-sectional studies are helpful for determining the prevalence of an outcome in a population.
Cohort studies instead recruit participants based on their exposure status. Cohort studies are longitudinal. They follow participants over time to observe the effect of this exposure (e.g., how many people who were exposed to asbestos go on to develop lung cancer). Cohort studies are helpful for establishing cause-and-effect relationships.
Continue reading: What is the difference between a cross-sectional study and a cohort study?
Case-control and cross-sectional studies differ in how participants are recruited and the types of questions they can answer.
In a case-control study, participants are recruited based on outcome status. Data are collected from two groups. The “case” group has an outcome of interest (e.g., a diabetes diagnosis), and the “control” group does not. These groups can be compared to understand what differences may have contributed to the outcome.
In a cross-sectional study, a sample of participants is recruited from a population without considering outcome status (often using random sampling). Data on outcomes and risk factors are then collected simultaneously from the sample. Cross-sectional studies are helpful for assessing the prevalence of an outcome.
Continue reading: What is the difference between a case-control study and a cross-sectional study?
In a cross-sectional study, researchers collect data from individuals at a single point in time.
In a longitudinal study, researchers collect data from individuals repeatedly or continuously over an extended period of time (often years).
Cross-sectional studies are faster and less expensive to conduct than longitudinal studies. However, because they collect data at a single point in time, cross-sectional studies are not the best option for establishing cause-and-effect relationships.
A common practice is to conduct a cross-sectional study to generate hypotheses. You can then use this information to design a longitudinal study.
Continue reading: What is the difference between a cross sectional study and a longitudinal study?
A Likert-type scale resembles a Likert scale—the respondent is presented with a series of statements, and they select their response from a set of ranked options.
However, for a true Likert scale, the respondent rates their level of agreement with these statements using a 5- or 7-point scale. Likert-type scales may instead ask people to rate constructs like frequency, satisfaction, or likelihood.
An example of a true Likert scale item is as follows:
Please rate your agreement with the following statement: I am most productive in the morning.
- Strongly disagree
- Disagree
- Neither agree nor disagree
- Agree
- Strongly Agree
A Likert-type scale may include items such as the following:
How frequently do you wake up before 8 a.m.?
- Never
- Rarely
- Sometimes
- Often
- Always
Continue reading: What is a Likert type scale?
Though traditional Likert scales include a 5-point response scale, some research has indicated that 7-point scales provide more reliable results.
As a rule of thumb, 5-point scales are better for unipolar constructs, which range from zero to positive, such as frequency. You may want to use 7-point scales for bipolar (or dichotomous) constructs that range from negative to positive, such as quality—some evidence suggests that doing so can increase reliability.
Continue reading: Should I use a 5- or 7-point Likert scale?
The term Likert scale is commonly mispronounced. The correct pronunciation is “Lick-urt,” not “Lie-kert.” The scale is named after its creator, Rensis Likert, and this is how you correctly say his last name.
Continue reading: How do you pronounce Likert scale?
