Validitas Internal dalam Eksperimen
Summary
TLDRThis video script explores the concept of internal validity in experiments, focusing on how researchers can determine causal relationships between variables. It explains the importance of ensuring that the independent variable (A) leads to changes in the dependent variable (B), and that there are no alternative explanations for this relationship. The script also introduces the terms 'local validity' and 'molar validity,' explaining that internal validity is context-dependent and varies with the complexity of the intervention being studied. Finally, the script touches on threats to internal validity and encourages further discussion on these concepts.
Takeaways
- 😀 Statistical conclusion validity focuses on ensuring accurate use of statistical methods to establish relationships between variables (independent and dependent).
- 😀 Internal validity ensures that the observed relationship between variables (A and B) is causal, not just a correlation.
- 😀 For a valid causal conclusion, three requirements must be met: A must precede B, A and B must be correlated, and there must be no alternative explanations for the relationship.
- 😀 Gembel's view on internal validity challenges the idea of reproducibility and generalizability, emphasizing that internal validity concerns the causal relationship within a specific context.
- 😀 'Local' validity refers to causal conclusions that apply to specific conditions, treatments, or time frames, while 'molar' validity refers to complex, multivariate treatments in experiments.
- 😀 Molar conditions are more complex and involve multiple components, such as psychotherapy, which includes different intervention types, timings, and settings.
- 😀 Psychotherapy, as an example of a molar condition, consists of various components like verbal interventions, non-verbal cues, therapist characteristics, and therapy settings.
- 😀 Valid conclusions in molar conditions must consider all these components and how they interact in a broader experimental setting.
- 😀 Internal validity is critical for establishing causal relationships within an experiment, but its scope is often limited to the context and time frame of the study.
- 😀 Threats to internal validity are factors that undermine the assumption of a causal relationship, and these will be discussed in future videos.
Q & A
What is statistical conclusion validity, and why is it important in research?
-Statistical conclusion validity refers to the use of appropriate statistical methods to make accurate conclusions about the relationship between independent and dependent variables. It is important because it helps ensure that the results of an experiment are based on reliable statistical analysis, establishing whether the variables are truly correlated.
What is internal validity, and how does it differ from statistical conclusion validity?
-Internal validity is concerned with whether a causal relationship exists between the independent and dependent variables in an experiment. Unlike statistical conclusion validity, which focuses on the statistical relationship, internal validity looks at whether the changes in the dependent variable are truly caused by the independent variable, without being influenced by other factors.
What are the three key conditions required to establish internal validity?
-The three key conditions required to establish internal validity are: 1) The independent variable (A) must precede the dependent variable (B); 2) There must be a covariance between A and B; and 3) No alternative explanations should exist that could account for the observed relationship.
According to Cook and Campbell, what is the proper understanding of internal validity?
-Cook and Campbell argue that internal validity is not about reproducibility, generalizability, or target population conclusions. It focuses specifically on ensuring that the causal relationship between variables within the specific experimental context is accurate and not influenced by external factors.
What is the concept of 'local validity' in the context of internal validity?
-Local validity refers to the idea that causal conclusions are valid within a specific, limited context, including the experimental setting, time, and the treatment or unit being studied. These conclusions are not meant to be generalized beyond the particular conditions of the experiment.
What does 'molar validity' mean in experimental research?
-Molar validity refers to the complexity of the experimental treatment, which involves multiple, interacting variables. It often applies to studies where the treatment is multivariate and consists of various components, such as psychotherapy, which includes different types of interventions, settings, and factors.
How does the concept of molar validity apply to psychotherapy studies?
-In psychotherapy studies, molar validity is important because psychotherapy involves various components, such as different types of interventions (verbal, nonverbal), settings, and factors like the therapist's office or patient expectations. These factors interact, making the treatment complex and multivariate.
What is the main challenge when dealing with molar validity in research?
-The main challenge with molar validity is that it involves complex, multifaceted treatments or conditions, which makes it difficult to isolate specific factors that contribute to the observed outcomes. Researchers must consider how these different components interact to form the overall treatment effect.
Why is internal validity considered important in experimental research?
-Internal validity is crucial because it ensures that the conclusions drawn from an experiment accurately reflect causal relationships between variables. Without internal validity, researchers cannot confidently claim that changes in the dependent variable are caused by the independent variable rather than by other factors.
What are some potential threats to internal validity in experiments?
-Threats to internal validity include extraneous variables, biases, or alternative explanations that could account for the observed relationship between the independent and dependent variables. These threats undermine the ability to draw causal conclusions from the experiment.
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