代做PSYC7901: Evaluating Research Designs帮做R语言

日期：2025-09-30 04:28

PSYC7901: Evaluating Research Designs

Research Design Considerations

When developing and evaluating a research design, these are the key points to consider:

•   Confidence in IVs and DVs as operationalised

•   Representativeness (and thus, generalisability) of the study population

•   Representativeness (and thus, generalisability) of the experimental context/environment

Considering the independent variable (IV)

Does the experiment as designed successfully manipulate what you intend to manipulate?

1.   What is the IV and what are its levels?

2.   How is the IV manipulated? (and is that appropriate for this type of IV?)

3.   Are the levels of the IV appropriate for comparisons that can test the stated hypotheses?

4.   Is there anything that might influence the impact ofthe IV on the outcomes beyond that of the intended manipulation of the IV? (i.e. potential confounds or biases, see below sections on the sample and the experiment context)

Considering the dependent variable (DV)

Does the experiment as designed successfully measure what you intend to measure?

1.   What is the DV construct (theoretical DV)?

2.   How is the DV construct operationalised so that it can be measured?

3.   Does the operational definition of the DV construct make sense?

4.   Does the measure actually measure what you intend (validity)?

5.   Are the measurements likely to be similar between trials or observers (reliability)?

6.   Can the measure actually detect differences or effects that might exist (sensitivity)?

Considering the sample

Are the participants recruited for the study (the sample) likely to show the same results as the target population of interest? i.e. Would you expect the results from this sample to be representative of the results you would expect from the broader population of interest?

1.   What are the characteristics of the participants in the sample and do they match the broader population of interest? (e.g. age, culture, language, gender, education level, etc).

2.   How are the participants recruited? Any inclusion/exclusion criteria?

3.   Could any particular demographic factors influence the pattern of results?

•   Particular demographic characteristics of the sample, if different from the population, could influence the outcomes ofthe study, providing alternate explanations.

4.   Are the characteristics of the participants in each condition (each level of the IV) similar?

•   For independent-samples designs, assigning participants at random to different

conditions or matching participants between groups on important demographic factors reduces the potential for this kind of confound between conditions.

•   Repeated-measures designs control this type of confound.

Considering the experimental context/environment

How confident are you that the phenomena or effects tested in this particular experiment context/environment would be similar in the general or real-world situation of interest? i.e. Would you expect the results in this particular experiment situation to be representative of the results you would expect in the real-world context/environment of interest?

1.   What is the context/environment in the experiment and does it match the broader context/environment of interest?

•   Contexts include factors such as physical location, time-of-day, social factors such as being observed or participating with others, moods or emotions, etc.

2.   What are the stimuli and how are they used in the task/s?

3.   Could any particular aspect of the context/environment or specific stimuli of the experiment influence the pattern of results?

•   Particular aspects of the experimental situation or stimuli used, if different from the general real-world situation of interest, could influence the outcomes ofthe study, providing alternate explanations.

•   Would you expect the same pattern of results with more general or “real world” situations or stimuli? Why or why not?

4.   Are the contexts/environments in each condition (each level of the IV) similar?

•   If there are differences in the context/environment between conditions, how could this impact results and what could be alternative explanations for the results?

•   For repeated-measures designs, participant context factors such as level of practice on the task or level of fatigue throughout the experiment can vary between conditions and need to be controlled by counter-balancing.