In a posttest only nonequivalent groups design, why are researchers unable to make definitive causal claims even if they carefully select comparison groups that share key characteristics?

In a posttest only nonequivalent groups design, selecting comparison groups that share key characteristics guarantees the elimination of all confounding variables.

A researcher is evaluating the effectiveness of a new 'Growth Mindset' workshop by comparing two nonequivalent middle schools. To improve the internal validity of this posttest-only design, the researcher intentionally selects schools that share specific traits. Match each selection strategy to the specific confounding variable it is intended to control.

A researcher is comparing two pre-existing groups to evaluate an intervention, matching them on baseline characteristics to improve the study's validity. Arrange the logical steps of the researcher's analytical process in the correct order, from identifying threats to determining the final level of causal certainty.

Imagine you are tasked with designing a study to evaluate the impact of a new 'Interactive Learning' software across two different middle schools using a posttest only nonequivalent groups design. To maximize internal validity by constructing a comparison that controls for major confounds, which set of criteria should you prioritize when selecting the control school?

When researchers select comparison groups that share similar traits to reduce confounds in a research design without random assignment, match each term with its correct description based on research methods principles.

A researcher evaluates a new teaching method by comparing two classrooms matched for baseline scores and teacher experience. Despite these controls, a scientific evaluator would judge the internal validity of this design as _____ because the lack of random assignment prevents the elimination of unmeasured variables.

A researcher wants to evaluate a new reading intervention using a posttest only nonequivalent groups design. She selects two classrooms from the same school, matched on baseline reading scores and teacher certification level. Because she controlled for these two key variables, she can now make definitive causal claims that the intervention caused any observed differences in posttest scores.

A researcher studying the effect of a school-based mindfulness program selects two pre-existing student groups matched on prior stress scores and socioeconomic status. An analyst reviewing this quasi-experiment would note that deliberately matching groups on these variables improves _____, but cannot substitute for true random assignment when drawing causal conclusions, because unmeasured confounds may still differ between the groups.

A colleague asks you to critique a posttest only nonequivalent groups study comparing two pre-existing classrooms on a new tutoring method. Arrange the following evaluative steps in the order you would logically apply them to judge whether the study's causal claims are justified.

Explain how researchers can control for confounding variables in a posttest only nonequivalent groups design to improve its internal validity, and recall the primary limitation that remains regarding causal claims.

Based on the provided context, diagnose whether the researcher can definitively conclude that the reading intervention caused any observed differences in posttest reading scores, and justify your answer by explaining how the classroom selection choices affect the study's validity.

Apply the control techniques of a posttest only nonequivalent groups design to a hypothetical study comparing a new math tutoring app across two pre-existing classes: list at least two specific baseline characteristics you would match between the classes to enhance validity, and explain why you still cannot claim the app caused any final differences.