Power calculations to get sample size needed to run an experiment

In summary, the speaker is conducting an experiment in development/experimental economics to see how household bargaining power affects the amount of money spent on children. They are struggling with power calculations and using STATA to compare proportions between three treatments. They plan to compare each treatment with each other. The speaker is unsure if their method is correct and is seeking additional help.
  • #1
Charlotte87
21
0
Hi everyone!

I am writing a paper in development/experimental economics concerning how household bargaining power (i.e. how much say the husband and wife has about how to spend household income) affect how much money is spent on children. I am going to conduct an experiment and is now in the phase of doing some power calculations in order to see how large sample I need. Unfortunately, I am having some problems doing these power calculations. I understand their purpose and everything, but I do not really see how I should use STATA to do the correct calculations.

I am doing a between-subject design with three treatments. In each treatment the money available will be varying. So, I think I need to do power calculations where I compare proportions since I will be comparing the share of money spent on children in each treatment group.

Even though I have three treatments, I will only compare two-and-two treatments. I will compre treatment 1 with treatment 2, treatment 1 with treatment 3 and treatment 2 with treatment 3. So far I have used the following command in STATA:

sampsi 0.1 0.3, power(0.9)

The significance level is then automatically 0.05, and 0.1 and 0.3 is proportions (i.e here the share of money spent on children). Does this make sense??

I have made a table comparing proportions from 0 to 1 (with a 0.1 intervals) and made a table, but I am still not sure whether my method is correct.
 
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  • #2
I'm sorry you are not finding help at the moment. Is there any additional information you can share with us?
 

1. How important are power calculations in experimental design?

Power calculations are crucial in experimental design as they determine the appropriate sample size needed to detect a statistically significant effect. This ensures that the experiment has enough power to accurately detect the effect being studied and increases the chances of obtaining meaningful and reliable results.

2. What factors are considered in power calculations?

In power calculations, factors such as the desired level of significance, effect size, and statistical power are taken into account. These factors help determine the minimum sample size needed to achieve a desired level of power for the experiment.

3. How do you calculate the power of an experiment?

The power of an experiment can be calculated using statistical software or by using a power calculator. These tools take into account the factors mentioned above and provide the required sample size for the experiment. It is important to note that the power of an experiment can also be influenced by other factors such as the research design and data analysis methods.

4. Can power calculations be done after the experiment has been conducted?

Ideally, power calculations should be done before the experiment is conducted to determine the appropriate sample size. However, if the experiment has already been conducted, power calculations can still be done to assess the sensitivity of the results and determine if the sample size was sufficient to detect the desired effect.

5. Are power calculations necessary for all experiments?

Power calculations may not be necessary for all experiments, especially for small-scale or exploratory studies. However, for experiments that aim to make statistically significant conclusions, it is important to perform power calculations to ensure the validity and reliability of the results.

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