Critical Eval Weeks 5-7
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Questions and Answers

What are the four basic elements contained in an experimental design?

  • Manipulation, Measurement, Comparison, Control (correct)
  • Observation, Measurement, Analysis, Reporting
  • Control, Measurement, Evaluation, Observation
  • Manipulation, Analysis, Comparison, Coordination
  • How is a quasi-experimental design different from an experimental design?

  • Quasi-experimental groups are created through random assignment.
  • Quasi-experimental designs have a control group.
  • Quasi-experimental designs do not involve the manipulation of variables.
  • Quasi-experimental designs cannot account for assignment bias. (correct)
  • Which of the following problems in establishing causation relates to changes in one variable that are accompanied by changes in many other variables?

  • The correlational problem
  • The sampling problem
  • The directionality problem
  • The third-variable problem (correct)
  • Which method involves ensuring that a specific variable remains unchanged to address internal validity?

    <p>Holding a variable constant</p> Signup and view all the answers

    What issue arises from the relation between depression and insomnia as described in the content?

    <p>The directionality problem</p> Signup and view all the answers

    Which of the following is NOT a method of actively controlling for extraneous variables?

    <p>Random sampling of the population</p> Signup and view all the answers

    What can occur when extraneous variables influence both the independent and dependent variables?

    <p>The confounding variable problem</p> Signup and view all the answers

    In which type of design does a researcher examine changes in behavior related to age through different groups of individuals?

    <p>Cross-sectional design</p> Signup and view all the answers

    What is the primary role of a systematic review in research?

    <p>To critically appraise all available evidence</p> Signup and view all the answers

    Which statistical test should be used for comparing the means of more than two groups?

    <p>Analysis of variance (ANOVA)</p> Signup and view all the answers

    How does a meta-analysis differ from a traditional literature review?

    <p>Meta-analysis combines results quantitatively from multiple studies</p> Signup and view all the answers

    Which statistical test is appropriate for comparing two groups’ medians with ordinal-level data?

    <p>Mann-Whitney's U test</p> Signup and view all the answers

    In evidence-based practice (EBP), how should a patient's preference be evaluated?

    <p>It should be of primary importance if the patient is fully informed.</p> Signup and view all the answers

    What is the purpose of conducting statistical calculations in a meta-analysis?

    <p>To calculate effect sizes and confidence intervals</p> Signup and view all the answers

    Which test is suitable for comparing proportions in different categories?

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

    A researcher is evaluating two independent groups' means. Which statistical test should they employ?

    <p>Independent-samples t-test</p> Signup and view all the answers

    What is a key characteristic of a systematic review compared to a traditional literature review?

    <p>Having operationalized criteria for study inclusion</p> Signup and view all the answers

    If a study involves a dependent outcome variable, which statistical test would be appropriate?

    <p>Dependent samples t-test</p> Signup and view all the answers

    What characterizes a factorial design?

    <p>It can have two or more independent variables.</p> Signup and view all the answers

    Which of the following statements accurately describes an effect size?

    <p>It quantifies the strength of a relationship.</p> Signup and view all the answers

    In a multiple-baseline design, what is a primary feature?

    <p>Treatment is applied in a staggered fashion across different baselines.</p> Signup and view all the answers

    What does a p-value less than 0.05 generally indicate?

    <p>There is strong evidence against the null hypothesis.</p> Signup and view all the answers

    What is the primary purpose of inferential statistics?

    <p>To draw conclusions about a population based on a sample.</p> Signup and view all the answers

    Which design involves observing the same subjects under different conditions?

    <p>Within-subjects design</p> Signup and view all the answers

    In the context of hypothesis testing, which statement defines the null hypothesis?

    <p>It indicates no effect or relationship within the population.</p> Signup and view all the answers

    What is a key ethical concern associated with the ABAB design?

    <p>It may require withdrawal of treatment from participants.</p> Signup and view all the answers

    How is effect size commonly quantified?

    <p>Through standardized measures like Cohen's d.</p> Signup and view all the answers

    What is the relationship between internal and external validity in nonexperimental and correlational studies?

    <p>Both have low internal validity and high external validity.</p> Signup and view all the answers

    What does a main effect refer to in a factorial design?

    <p>The influence of a single factor across levels.</p> Signup and view all the answers

    What type of design is characterized by a series of treatments applied to the same subjects over different phases?

    <p>Repeated measures design</p> Signup and view all the answers

    What is one major limitation of single-case research studies?

    <p>They often lack generalizability due to low participant numbers.</p> Signup and view all the answers

    What is the main purpose of descriptive statistics?

    <p>To summarize and describe the characteristics of a dataset.</p> Signup and view all the answers

    Study Notes

    Experimental Designs

    • Experimental designs have four basic elements: manipulation, measurement, comparison, and control.
    • Nonexperimental and quasi-experimental designs do not manipulate independent variables, making them vulnerable to assignment bias.
    • Assignment bias: occurs when participants in different groups have different characteristics that could influence the outcome of the study.
    • The researcher does not create groups in nonexperimental and quasi-experimental designs, leading to assignment bias.
    • True experiments utilize randomization to reduce assignment bias.
    • Control: refers to the ability to eliminate or minimize the effects of extraneous variables that might influence the dependent variable.

    Threats to Internal Validity

    • Nonexperimental and quasi-experimental studies are always susceptible to threats to internal validity.
    • Internal validity: the extent to which we can be confident that the independent variable caused the observed changes in the dependent variable.
    • Two primary types of developmental research designs: cross-sectional and longitudinal.
    • Cross-sectional design: compares different age groups at a single point in time,
    • Longitudinal design: tracks the same group of participants over time.

    Problems in Establishing Causation

    • The third variable problem: when changes in one variable are accompanied by changes in other variables, making it difficult to determine the true cause of the effect.
    • The directionality problem: when it is unclear which variable is causing the change in the other, even if a correlation exists.
    • Controlling nature: strict controls are necessary to isolate the effects of the independent variable and establish causation.

    Extraneous and Confounding Variables

    • Extraneous variables: any variables that are not of primary interest but could potentially influence the dependent variable.
    • When extraneous variables impact both the independent and dependent variables, they become confounding variables.
    • Environmental variables: aspects of the physical environment that might affect the results of the study.
    • Individual differences: characteristics of participants that vary and might influence the dependent variable.
    • Time-related variables: changes that occur over time that might influence the dependent variable.

    Actively Controlling for Extraneous Variables

    • Three methods for actively controlling extraneous variables:
      • Holding a variable constant: ensures that all participants experience the same level of a particular variable.
      • Matching across treatment conditions: ensures that groups are similar on a specific variable.
      • Control by randomization: ensures that participants are randomly assigned to different groups, minimizing the effects of extraneous variables.

    Internal vs. External Validity

    • Holding a variable constant strengthens internal validity but can limit external validity.
    • Simulation experiments aim to increase external validity by replicating real-world situations, but they might have lower internal validity than controlled experiments.
    • Field studies, conducted in natural settings, often have higher external validity but lower internal validity compared to laboratory experiments.

    Factorial Designs

    • Factorial design: a type of experiment that includes two or more independent variables or factors.
    • Factors: independent variables that are manipulated in a factorial design.
    • Main effect: the effect of a single factor on the dependent variable, averaged across the levels of the other factors.
    • Interaction: occurs when the effect of one factor on the dependent variable depends on the level of the other factor.

    Types of Experimental Designs

    • Between-subjects design: participants are randomly assigned to different conditions.
    • Within-subjects design or repeated measures design: each participant experiences all conditions of the independent variable.
    • Mixed design: a combination of between-subjects and within-subjects designs.

    Descriptive and Inferential Statistics

    • Descriptive statistics: used to summarize and describe data.
    • Inferential statistics: used to draw conclusions about a population based on a sample of data.
    • Descriptive statistics: provide basic information about variables and highlight potential relationships between them.
    • Inferential statistics: use sample information to make general conclusions about the population.

    Null and Alternative Hypotheses

    • Null hypothesis (H0): a statement about the population indicating no effect, no change, no difference, or no relationship.
    • Alternative hypothesis (H1): the research hypothesis that there is an effect, change, difference, or relationship.

    P-Values

    • A p-value represents the probability of observing the data if the null hypothesis is true.
    • p < 0.05: indicates a statistically significant result, suggesting that the observed data is unlikely to have occurred by chance if the null hypothesis were true.

    Effect Size

    • Effect size: a standardized measure of the magnitude of an observed effect, independent of sample size.
    • Cohen's d: a common effect size statistic for the difference between means.
    • Pearson's correlation coefficient (r): a common effect size statistic for the strength of a linear relationship.

    Single-Case Research Studies

    • Single-case research studies focus on a single participant or a small number of participants.
    • To qualify as an experiment, single-case studies must involve:
      • Manipulation of the independent variable.
      • Strict control of extraneous variables.
    • Visual inspection: evaluates the results of single-case studies using graphs to determine if the changes in the dependent variable are substantial enough to be considered a large effect.

    ABAB Design

    • ABAB design: a single-case design consisting of four phases: baseline (A), treatment (B), baseline (A), treatment (B).
    • Ethical concern: it can be difficult to justify withdrawing effective treatment in the second baseline phase, especially if it impacts the participant's well-being.

    Multiple-Baseline Design

    • Multiple-baseline design: consists of a series of A-B designs stacked on top of one another, with each baseline phase progressively longer.
    • The treatment is applied to different target variables, participants, or settings in a staggered fashion.
    • Strength of the multiple-baseline design: it eliminates the need to withdraw treatment to demonstrate its effectiveness, which is particularly beneficial in settings where treatment withdrawal is not ethical or practical.

    Statistical Tests

    • Independent-samples t-test: compare means of two groups for between-subjects designs with a continuous dependent variable.
    • Analysis of variance (ANOVA): compare means of more than two groups for between-subjects designs with a continuous dependent variable.
    • Dependent samples t-test: compare means of two groups for within-subjects designs with a continuous dependent variable.
    • Chi-square test: analyze categorical data to compare proportions between different groups.
    • Mann-Whitney U test: compare medians of two groups with an ordinal dependent variable.
    • Kruskal-Wallis test: compare medians of more than two groups with an ordinal dependent variable.

    Systematic Reviews and Meta-Analyses

    • Systematic reviews: summarize all available evidence on a topic by critically appraising studies, using a rigorous and standardized method for selection, data extraction, and analysis.
    • Meta-analysis: statistically combines the results from multiple studies to generate a quantitative estimate of the overall effect.
    • A primary difference between a systematic review and a meta-analysis: a systematic review summarizes evidence, while a meta-analysis combines data to calculate an overall effect.

    Patient Preferences in EBP

    • The ethical principles of autonomy and beneficence should guide clinical decision-making.
    • A fully informed patient's preferences should be of primary importance.
    • However, when multiple efficacious treatments are available, compelling evidence suggesting substantial superiority of one approach over others should be considered.

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    Description

    This quiz covers key concepts in experimental designs, including manipulation, measurement, and control. It also addresses the significance of internal validity and the threats posed by nonexperimental and quasi-experimental designs. Test your understanding of how assignment bias affects research outcomes.

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