Quantitative Research Design

Vocabulary flashcards covering key concepts, designs, considerations, classifications, and validity aspects of quantitative research design.

Quantitative Research Design

A plan for answering the research question, including study setting, participant selection, study procedures, variable measurement, data collection, data management, and data analysis.

Intervention (Consideration)

A factor regarding manipulations of independent variables to consider in quantitative research design.

Comparisons (Consideration)

A factor regarding the groups being compared to consider in quantitative research design.

Confounding Variables

Variables that could obscure or distort the relationship between the independent and dependent variables, requiring consideration in research design.

Controlling Participant Factors

Methods such as randomization, homogeneity, matching, and statistical control used to manage differences among study participants.

Blinding

A procedure to prevent participants, researchers, or data collectors from knowing group assignments to reduce bias.

Cross-sectional Data Collection

Data collected at a single point in time.

Longitudinal Data Collection

Data collected over an extended period, involving multiple data collection points.

Prospective Timing

Research where data collection moves forward in time from presumed cause to presumed effect.

Retrospective Timing

Research where data collection moves backward in time from presumed effect to presumed cause.

Systematic Review

The highest level of evidence (Level I) for therapy questions, synthesizing findings from multiple studies.

Single Randomized Controlled Trial (RCT)

Level II evidence for certain etiology questions.

Single Non-Randomized Trial (Quasi-Experiment)

A study design lacking full randomization but includes an intervention and control.

Single Prospective Cohort Study

Level II evidence for prognosis and some diagnosis questions, following a group forward in time.

Single Case-Control Study

A retrospective study design comparing individuals with a condition (cases) to those without (controls).

Single Cross-Sectional Study (e.g., Survey)

Level II evidence for descriptive quantitative questions, collecting data at one point in time.

Single In-Depth Qualitative Study

Level II evidence for meaning/process questions, exploring phenomena in depth.

Experimental Designs

Research designs characterized by intervention, control, and randomization to establish cause-and-effect relationships.

Quasi-experimental Designs

Research designs that include an intervention and control but lack randomization of participants.

Nonexperimental Designs

Research designs that observe, describe, and document phenomena without researcher intervention, control, or randomization.

Intervention (Experimental Element)

The manipulation of the independent variable by the researcher in an experimental study.

Control (Experimental Element)

The inclusion of a group that does not receive the experimental intervention or receives a standard treatment.

Randomization (Experimental Element)

The random assignment of participants to experimental or control groups to ensure equal distribution of extraneous variables.

Post-test Only Design

An experimental research design where participants are randomized, an intervention is applied to one group, and the outcome is measured after the intervention in both groups.

Pre-test – Post-test Design

An experimental research design where participants are randomized, outcomes are measured before (pre-test) and after (post-test) the intervention for both experimental and control groups.

Crossover Design

An experimental design where participants receive all interventions in a randomized order over different periods, acting as their own control.

Advantages of Experimental Designs

Primarily used for testing cause-and-effect relationships with high internal validity.

Disadvantages of Experimental Designs

May face challenges with practical significance versus control, generalizability, and the necessity of randomization.

Nonequivalent Control Group Post-test Only Design

A quasi-experimental design with an intervention group and a non-randomized control group, where outcomes are measured only after the intervention.

Nonequivalent Control Group Pre-test – Post-test Design

A quasi-experimental design using an intervention group and a non-randomized control group, where outcomes are measured both before and after the intervention.

One Group Pre-test – Post-test Design

A quasi-experimental design with a single group measured before and after an intervention, lacking a control group for comparison.

Time Series Design

A quasi-experimental design involving multiple pre-test and post-test measurements over an extended period for a single group or multiple non-randomized groups.

Advantages of Quasi-experimental Designs

Practical, more acceptable to participants, and can be used when randomization is unethical or impossible.

Disadvantages of Quasi-experimental Designs

More difficult to make definitive causal inferences due to the lack of randomization.

Correlation Studies

Nonexperimental designs that investigate relationships between variables without manipulation; correlation does NOT prove causation.

Cohort Design

A nonexperimental design where a group of individuals exposed to a certain factor is followed over time to observe the development of outcomes.

Case-Control Design

A nonexperimental design that compares individuals with a disease or outcome (cases) to similar individuals without the disease or outcome (controls) to identify past exposures or characteristics.

Descriptive Studies

Nonexperimental designs that observe, describe, and document a phenomenon without manipulating variables or seeking to establish cause-and-effect.

Advantages of Nonexperimental Designs

Very practical, efficient way to collect large amounts of data, and useful for studying phenomena in natural settings.

Disadvantages of Nonexperimental Designs

Cannot make causal inferences and are susceptible to self-selection bias.

Critiquing a Quantitative Study Design

The process of evaluating whether the study design matches the research question/hypothesis, and identifying its strengths and limitations.

Statistical Conclusion Validity

The extent to which the conclusions about the relationships between variables based on statistical evidence are accurate.

External Validity

The extent to which the findings of a study can be generalized to other populations, settings, and times.

Construct Validity

The extent to which the variables in a study accurately measure the theoretical constructs they are intended to represent.

Internal Validity

The extent to which a causal inference between an independent and dependent variable is free from the influence of confounding factors.

Temporal Ambiguity (Threat to Internal Validity)

A threat to internal validity where the direction of causality between the independent and dependent variables is unclear.

Selection (Threat to Internal Validity)

A threat to internal validity caused by pre-existing systematic differences between groups that could account for observed effects.

History (Threat to Internal Validity)

A threat to internal validity referring to external events occurring during the study that could affect the dependent variable.

Maturation (Threat to Internal Validity)

A threat to internal validity referring to changes within participants over time (e.g., growth, fatigue) that could affect the dependent variable.

Mortality/Attrition (Threat to Internal Validity)

A threat to internal validity caused by the differential loss of participants from study groups, which can lead to biased results.