Point estimate from multiple sampling distributions

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SUMMARY

The discussion focuses on estimating a single point estimate and confidence intervals for the parameter θ from two experimental groups, A (n=5) and B (n=8), using Markov-chain Monte-Carlo (MCMC) methods. The posterior distributions for θ are approximately normal but slightly right-skewed. The user, capy_bara, seeks guidance on the best method to summarize these distributions, noting discrepancies between averaging means and medians. The recommended approach is to use convolution to derive a point estimate and confidence level effectively.

PREREQUISITES
  • Understanding of Markov-chain Monte-Carlo (MCMC) methods
  • Familiarity with statistical concepts of point estimates and confidence intervals
  • Knowledge of normal and skewed distributions
  • Basic skills in statistical programming (e.g., R or Python)
NEXT STEPS
  • Research the application of convolution in statistical estimation
  • Explore methods for summarizing posterior distributions in Bayesian statistics
  • Learn about the implications of using means versus medians in data analysis
  • Investigate advanced MCMC techniques for better parameter estimation
USEFUL FOR

Researchers and statisticians working with Bayesian methods, particularly those involved in biological sample analysis and seeking to summarize complex distributions effectively.

capy_bara
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Dear all, I hope someone can help me.

I have two experimental groups, A (n=5) and B (n=8) containing biological samples. The samples are used to estimate my parameter of interest, θ. I do this with Markov-chain Monte-Carlo, which gives me a posterior distribution of θ for each of my samples. The distributions look approximately normal but are skewed a bit to the right. All values for θ are positive.
I wonder how I can now report single estimates (and confidence intervals) for θ in groups A and B, respectively.

Averaging the means of each distribution in one group gives me very different results than averaging the medians of all distributions. I also tried combining all distributions from one group and then taking the mean or the median. How can I find out which is the best way to summarize all distributions within one group to get a single point estimate?

I hope my problem is clear, I would appreciate any help.
Many thanks in advance,
capy_bara
 
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For each sample in A and B, you get a distribution of (possible) θ, and you want a single number and confidence interval for θ in A and B?

How can I find out which is the best way to summarize all distributions within one group to get a single point estimate?
Convolution, if nothing simpler works. This allows to get your point estimate and confidence level in a natural way.
 

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