7. RESEARCH METHODS (Reliability) Flashcards
What is reliability in psychology?
Reliability refers to the consistency of a measurement. If the same measurement or test is repeated, we should get the same result every time for the measurement to be considered reliable.
Why is reliability important in psychological research?
Reliability is crucial because it ensures that the results of research are consistent and replicable. If results are unreliable, the findings cannot be trusted or generalized.
What is internal reliability?
Internal reliability refers to the consistency within a test or measure. For example, in a personality test, if someone scores highly on one section, they should score similarly on other sections measuring the same trait.
What is external reliability?
External reliability refers to the ability to replicate the same results when the test is repeated on different occasions or with different participants, i.e., consistent results across time and people.
How can reliability be improved in experiments?
Reliability in experiments can be improved by:
* Standardization: Ensuring procedures are the same for every participant.
* Taking multiple measures: Repeating measurements to get an average, reducing anomalies.
* Pilot studies: Conducting pilot studies to identify any issues before the actual study.
What is test-retest reliability?
Test-retest reliability is when a test or procedure is repeated (usually at least twice) with the same participants, and their scores are compared. A high correlation between the two sets of scores suggests good reliability.
How is reliability assessed in an experiment?
Reliability is assessed by comparing participants’ scores across different testing occasions using statistical tests, such as correlation coefficients. A strong positive correlation suggests good reliability.
How can reliability be improved in observational studies?
Reliability in observational studies can be improved by:
* Operationalizing behavioral categories to ensure consistency.
* Training observers to use categories effectively.
* Standardizing data collection procedures.
* Conducting pilot studies to test for issues.
What is inter-observer reliability?
Inter-observer reliability refers to the extent to which different observers agree on their observations. High inter-observer reliability is achieved when there is strong agreement between observers’ recorded data.
How is inter-observer reliability assessed?
Inter-observer reliability is assessed by comparing the data recorded by different observers. If their observations correlate strongly (correlation coefficient of 0.80 or higher), reliability is considered good.
How can reliability in self-report methods (e.g., questionnaires or interviews) be improved?
Reliability in self-report methods can be improved by:
* Reducing ambiguity: Clarifying questions to avoid misinterpretation.
* Standardizing procedures, ensuring the same environment and interviewer style.
* Pilot studies: Testing the self-report measures to identify any issues before the full study.
What is the split-half method in reliability assessment?
The split-half method involves dividing a test into two halves and comparing the participant’s scores on both halves. A strong correlation between the two halves suggests the test is reliable.
How is reliability assessed in self-report methods?
Reliability is assessed in self-report methods by:
* Using test-retest reliability: Repeating the same test over time and comparing results.
* Using the split-half method: Comparing scores from two halves of the test.
How can reliability in self-report methods be assessed using inter-interview reliability?
Inter-interview reliability is assessed by comparing responses from the same participant interviewed at different times or by comparing responses from two different interviewers using the same approach.
What are the limitations of reliability in psychological research?
Limitations of reliability include:
* Observer bias: Different interpretations by researchers.
* Cultural bias: Interpretation of responses may vary depending on the researcher’s background.
* Artificial distinctions: Categories may be arbitrary, leading to missed behaviours.
