UGC NET Questions (Paper – 1)

Causal-comparative research, also called ex post facto, compares groups that already differ on a dependent variable or on a presumed cause to explore possible causal relationships. The researcher does not manipulate the independent variable but attempts to identify factors associated with existing differences. Because groups are not formed randomly, causal inferences are tentative and based on logic rather than strict control. Therefore, the non-experimental design described is correctly termed causal-comparative research.

Option A:
Survey research collects information from respondents using questionnaires or interviews to describe attitudes, behaviours or characteristics; it is not defined by comparing pre-existing groups for causal explanation. Thus, it does not match the stem.

Option B:
Causal-comparative designs use careful selection of groups and statistical controls to reduce alternative explanations, but they cannot fully equate groups the way true experiments with random assignment can. They are useful when manipulation is impossible or unethical. These features align with the description of comparing existing groups to explore causes, so this option is correct.

Option C:
Experimental research introduces treatments and random assignment to groups to test causal hypotheses under controlled conditions, which goes beyond simply observing existing groups. Hence, it is not the best fit here.

Option D:
Ethnographic research focuses on in-depth cultural description through prolonged fieldwork and participant observation rather than formal group comparisons to explore causal factors, so it does not complete the stem.

A cross-sectional study gathers data from a sample of individuals at one specific point in time, without following them over an extended period. It is often used to describe the prevalence of characteristics, attitudes or behaviours in different groups or to compare subgroups at that moment. Because measurements are taken only once, researchers cannot directly infer changes over time but can examine associations among variables. The stem clearly describes this one-time data collection, so cross-sectional study is the correct term.

Option A:
Longitudinal studies collect data from the same participants repeatedly over extended periods to track changes and developmental trends. They involve multiple time points rather than a single point, making them distinct from cross-sectional designs. Since the stem explicitly mentions a single point in time, longitudinal study cannot be the right answer.

Option B:
Cross-sectional designs are common in survey research where researchers want a snapshot of conditions or attitudes in a population. For example, a cross-sectional survey might compare research attitudes of first-year and final-year students at the same time. This matches the description in the stem, which focuses on describing or comparing groups based on one-time data collection.

Option C:
Experimental studies manipulate one or more independent variables and typically involve control groups and random assignment to test causal hypotheses. While they may be conducted within a limited time frame, their defining feature is manipulation and control, not merely one-time data collection from different individuals. Thus, experimental study is not the best label for the design described.

Option D:
Case-control studies are usually retrospective, comparing individuals with a particular condition (cases) to those without it (controls) to explore possible risk factors. Although case-control designs may gather data at one time, they have a specific focus on past exposures and are often used in epidemiology. The broader description in the stem fits the generic cross-sectional design better than the more specialised case-control approach.