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Using examples! Discuss any two threats to validity?
joyline yegon
more than 1 week ago
Using examples! Discuss any two threats to validity?
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ChatGPT
more than 1 week ago
1. Selection bias: This occurs when the sample selected for a study is not representative of the population being studied. For example, if a study on the effectiveness of a new medication only includes participants who are already in good health, the results may not be applicable to the general population. This can lead to an overestimation or underestimation of the true effect of the intervention.
2. Measurement bias: This occurs when the tools or methods used to measure the variables of interest in a study are inaccurate or unreliable. For example, if a study relies on self-reported data from participants, there may be a risk of social desirability bias, where participants provide responses that they believe are socially acceptable rather than truthful. This can lead to an overestimation or underestimation of the true relationship between variables.
2. Measurement bias: This occurs when the tools or methods used to measure the variables of interest in a study are inaccurate or unreliable. For example, if a study relies on self-reported data from participants, there may be a risk of social desirability bias, where participants provide responses that they believe are socially acceptable rather than truthful. This can lead to an overestimation or underestimation of the true relationship between variables.
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Google Gemini AI
more than 1 week ago
1. Selection Bias:
- Example: Researchers compare the academic performance of students who attend private schools to those who attend public schools. The results show that private school students outperform public school students.
- Threat to Validity: The results may not be valid because the students were not randomly assigned to private or public schools. Self-selection into private schools could be due to factors (e.g., higher parental income, greater motivation) that are associated with better academic performance, leading to an inflated estimate of the private school effect.
2. Experimental Mortality:
- Example: Researchers conduct an experiment to determine the effectiveness of a new drug on reducing cholesterol. Some participants drop out of the study before the end, and the results show that the drug significantly reduces cholesterol among those who remained.
- Threat to Validity: The results may not be valid because the participants who dropped out may have been different from those who remained (e.g., had higher baseline cholesterol levels). This could lead to a biased estimate of the drug's effectiveness.
- Example: Researchers compare the academic performance of students who attend private schools to those who attend public schools. The results show that private school students outperform public school students.
- Threat to Validity: The results may not be valid because the students were not randomly assigned to private or public schools. Self-selection into private schools could be due to factors (e.g., higher parental income, greater motivation) that are associated with better academic performance, leading to an inflated estimate of the private school effect.
2. Experimental Mortality:
- Example: Researchers conduct an experiment to determine the effectiveness of a new drug on reducing cholesterol. Some participants drop out of the study before the end, and the results show that the drug significantly reduces cholesterol among those who remained.
- Threat to Validity: The results may not be valid because the participants who dropped out may have been different from those who remained (e.g., had higher baseline cholesterol levels). This could lead to a biased estimate of the drug's effectiveness.
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