Quasi-Experimental Designs Quiz

<p>To determine the statistical significance of study results. (B)</p> Signup and view all the answers

<p>Chi-square test (B)</p> Signup and view all the answers

<p>Natural experiments occur naturally without intervention. (D)</p> Signup and view all the answers

<p>Interrupted time series analysis (C)</p> Signup and view all the answers

<p>It summarizes data to identify trends and anomalies. (C)</p> Signup and view all the answers

<p>They are conducted in naturalistic settings, enhancing external validity. (D)</p> Signup and view all the answers

<p>They may suffer from selection bias due to non-random assignment. (D)</p> Signup and view all the answers

<p>By comparing the employment rates of participants and non-participants. (D)</p> Signup and view all the answers

<p>To ensure the medication is effective by comparison. (A)</p> Signup and view all the answers

<p>A change in government policy impacting a community. (B)</p> Signup and view all the answers

<p>External factors influencing outcomes over time. (D)</p> Signup and view all the answers

<p>They can address ethical concerns by observing natural events. (A)</p> Signup and view all the answers

<p>To assess changes in the target behavior or outcomes. (C)</p> Signup and view all the answers

<p>Quasi-experimental design evaluates causal relationships without full control of the independent variable. (D)</p> Signup and view all the answers

<p>Non-equivalent control group design (B)</p> Signup and view all the answers

<p>It does not allow for control over other influencing factors. (B)</p> Signup and view all the answers

<p>Potential confounding factors. (D)</p> Signup and view all the answers

<p>Dependent variable changes over a specific event. (C)</p> Signup and view all the answers

<p>Did the intervention cause the change in the outcome? (D)</p> Signup and view all the answers

<p>To emulate randomized control trials when they are not feasible. (A)</p> Signup and view all the answers

<p>They receive the treatment or intervention being studied. (B)</p> Signup and view all the answers

<p>When investigating the effect of a naturally occurring event (A)</p> Signup and view all the answers

<p>Evaluating the effect of a natural disaster on community health (B)</p> Signup and view all the answers

<p>When ethical constraints prevent random assignments (D)</p> Signup and view all the answers

<p>They often lack randomization, which may introduce bias (D)</p> Signup and view all the answers

<p>The effectiveness of a public health campaign on behavior change (B)</p> Signup and view all the answers

<p>Examining the outcomes of a community-based intervention program (A)</p> Signup and view all the answers

<p>They allow for the investigation of non-manipulable variables (D)</p> Signup and view all the answers

<p>They lack random assignment to interventions (C)</p> Signup and view all the answers

<p>They are usually less expensive and easier to conduct. (A)</p> Signup and view all the answers

<p>Differences between groups that could affect study outcomes. (A)</p> Signup and view all the answers

<p>When evaluating programs or policies that have already been implemented. (C)</p> Signup and view all the answers

<p>Findings may be more applicable to varied populations and contexts. (A)</p> Signup and view all the answers

<p>By employing statistical techniques to control for confounding variables. (B)</p> Signup and view all the answers

<p>Difficulty in evaluating implemented policies. (B)</p> Signup and view all the answers

<p>Limitations in making causal inferences. (B)</p> Signup and view all the answers

<p>Studying the impact of a new educational policy in an existing school system. (B)</p> Signup and view all the answers

A research method used to study the impact of an intervention without random assignment.

Determining the effect of an intervention or treatment on a target issue.

A bias in a quasi-experimental design that arises when participants are not randomly assigned to groups.

The extent to which the results of a study can be generalized to other populations or settings.

A threat to validity in quasi-experiments where events outside the study affect the groups differently.

A threat to validity in quasi-experiments; participants changing naturally over time affecting the results.

Assessing the effectiveness of a job training program on participants' employment rate.

Measuring the impact a new policy has had on a particular region or area.

Quasi-experimental designs are used when it's not possible or ethical to randomly assign participants to groups. This is helpful when studying an intervention's effect.

In studies with small samples, quasi-experimental designs help evaluate the intervention's effect without large groups.

Quasi-experimental designs can study events like natural disasters or policy changes to see what impact they have.

For long-term programs or interventions, quasi-experimental designs help evaluate the sustained impact of those programs.

Quasi-experimental studies can examine the relationship between variables you can't directly manipulate, but that still affect outcomes.

An example of using quasi-experimental design to compare student performance with a new vs. traditional teaching method.

An example of assessing a public health campaign's effectiveness using a quasi-experimental design by comparing target populations with and without exposure to the campaign.

Quasi-experimental designs might not fully account for other factors affecting the study's results.

Quasi-experimental designs don't randomly assign participants to groups.

Quasi-experimental designs don't use random group assignments.

Difficulty in establishing a direct cause-and-effect relationship in the study because of lack of control.

Results from quasi-experimental studies might not apply to other situations or populations.

More practical and cost-effective, and often readily applicable to real-world situations with implemented programs or policies.

Uncertainty over cause-and-effect relationships, and the results might not be generalizable to wider contexts.

Researchers select similar groups, but one group receives the treatment, while the other doesn't. Outcomes are then compared.

Tracks a dependent variable over a period, including before and after an intervention. It observes changes.

Measures the dependent variable before and after an intervention, but without a control group.

The variable manipulated or changed by the researcher.

The variable measured to see if it's affected by the independent variable.

A gold standard experiment where participants are randomly assigned to groups.

A relationship where one variable influences another.

This design studies an intervention's effect by comparing participants on either side of a specific cutoff point on a continuous variable like a test score.

This design examines the effects of an intervention or event that happens naturally without the researcher's control. It's used when true experiments are not feasible or ethical.

This type of analysis summarizes collected data using measures like mean, median, mode, range, and standard deviation to identify trends or patterns.

This method uses statistical tests to determine if the study results are statistically significant. It helps generalize findings from a sample to a larger population.

This technique reduces bias in quasi-experimental designs by matching participants in the intervention group with those in the control group who have similar characteristics.

This analysis compares the difference in outcomes between two groups over time to determine if an intervention had an impact on the target population.

This technique examines the impact of an intervention by comparing data collected before and after the intervention. It helps determine the significant impact of the intervention on the target population.

This analysis compares the outcomes of participants who fall on either side of a predetermined cutoff point. It helps determine the intervention's significant impact on the target population.