Recent content by checkthebias

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    95% confidence interval using standard error of a proportion

    Betainv is the cumulative distribution function. Beta distribution has two shape parameters (alfa and beta), so you need to calculate the cumulative distribution function Betainv(0.975, alfa, beta).
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    Outlier analysis with IQR and different sample size

    Yes, i did it in the first article of the study, after truncate the distribution at the 98th percentile. In this specific case is theoretical. I'm not sure even if i have framed the problem in the exact manner. Because i have 15 distributions that have not independent metrics (if the average...
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    95% confidence interval using standard error of a proportion

    With rare events (p very high) you have to use the beta distribution in order to find the confindence interval, not the normal. https://onlinelibrary.wiley.com/doi/full/10.1002/pst.1901
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    Outlier analysis with IQR and different sample size

    Not sure that outlier detection serves only for those purposes. I think that it can serve also to "describe" the empirical distribution and if or not it is "well-behaved". For example if i generate two samples with n = 1000, one by a normal distribution and another by a t-student with df = 3...
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    Outlier analysis with IQR and different sample size

    I'm doing an extreme outlier analysis on the price distribution of the New York Airbnb listings in 2019. I divided the overall distribution in 15 distributions, grouping them by "room_type" (3 types) and "borough" (5 boroughes): for example, one distribution can be ("Private room", "Queens")...
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    Cross-section correlations in panel data

    Let's say we have 3 variables and T = 1000. Let's say we don't know if the variables follow a stationary or non-stationary process. We plot graphs and we see that variance seems not constant, so we prefere using the Kendall coefficient and not the Pearson. My question is: does it make sense to...
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    Is there a test for omitted variable bias?

    But in economics e financial world you are not in a laboratory...you receive the data from the markets or real world, period. For example: instrumental variables is a theoretical matter. It's not praticable in reality when you are inspecting a complex system as financial markets for example...
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    Is there a test for omitted variable bias?

    Forgive me if i could ask some trivial questions for who has a very strong background in statistics unlike me, but: First of all: In economics and finance the unconfoundness assumption is so implicit and so constant in EVERY paper. Imho that implicit assumption in order to make causal inference...
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    Is there a test for omitted variable bias?

    Could you explain that in more details please?
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    Is there a test for omitted variable bias?

    So...in a complex system (almost every real life inference problem is within a complex system), the omitted variable bias is almost certain. Not very well ...
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    Is there a test for omitted variable bias?

    I study finance and economics and every time i study an econometric study with OLS regression i wonder how the author can be sure of the non existance of omitted variable bias. I guess that in almost every economic study with regression this bias is present. Is there a method or test to check if...