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Confidence intervals, doesn't the definition suggest that it has a probability of e.g. 95% of containing the true value of the parameter?

As an illustration, consider the following method of producing a confidence interval: Based on some arbitrary random variable (e.g. rolling a dice) we output the interval $(-\infty,+\infty)$ with ...
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What is the impact of duplicate data on the variance of regression coefficient?

The coefficients themselves will no change. Imagine you perform the analysis on the first dataset, and plot the regression line with the datapoints around the regression line. Now what would happen if ...
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Confidence interval estimation in easy to understand way

Confidence intervals for the mean $\mu$ of a normal population based on a random sample of size $n$ from the population are of the type you mention. A 95% z-interval, if the population standard ...
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How many values should one validate to achieve a desired confidence?

There are a few ways to think about this. If you want to use the confidence interval approach, then you should also look at the "finite population correction" (Googling for that phrase ...
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Confidence interval for GLM or the maximum of a function?

In the comments there are good proposals, like the traditional delta method. A newer method which might be more exact, is constructing a profile likelihood confidence interval, which today is quite ...
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Correct Interpretation of Survival Curves

The type of inference you describe is one that would hinge on some implicit assumptions about the relationship between health risks and resources. Implicit in the suggestion to target funding to men/...
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4 votes

Correct Interpretation of Survival Curves

The answer is unfortunately no. These curves tell you about the survival profile of men and women under the standard of care. On the other hand, your question is asking about an alternative of care. ...
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Computing sample size for a sample to estimate binomial distribution when point estimate of proportion is 0

A Jeffreys 95% CI for the binomial proportion is based on the non-informative prior distribution $\mathsf{Beta}(.5,.5)$ and is said to give good frequentist results. Several other styles of Cis are in ...
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2 votes

Correct Interpretation of Survival Curves

I think that the answer is not easy and depends from a number of factors which cannot be captured only by the difference in survival curves. First: the situation depicted is uttermost theoretical and ...
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Correct Interpretation of Survival Curves

A somewhat sobering answer is that I believe these types of issues can often be ignored. For example, during grad school I did an internship at a large Pharma company. At one point, one of the senior ...
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Testing and conidence interval in a clinical trial

If you use statistical software to test the hypothesis $H_0: \mu_1 \le \mu_2$ against $H_a: \mu_1 > m_2$ you will typically get a 95% confidence interval for $\mu_1 - \mu_2$ as part of the output. ...
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4 votes

What does it mean if my confidence interval includes zero with a significant p value in linear regression analysis?

Thank you for the screenshot. The unstandardized coefficient is $-0.00108$ (rounded to three significant digits) with a corresponding 95% confidence interval of $(-0.00172; -0.000445)$ and a $p$-value ...
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How to test overlapping confidence intervals to see a significant difference between groups in a COX propotional model

This is no different from any comparison of regression coefficients in a model. See for example this page in the context of logistic regression. It's straightforward here, as ...
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confidence interval: A/B test - unable to decide what to use

I almost address how to do this here. The test statistic for a difference in proportions is $$ z=\frac{p_{1}-p_{2}}{\sqrt{\frac{p_{1}\left(1-p_{1}\right)}{n_{1}}+\frac{p_{2}\left(1-p_{2}\right)}{n_{2}}...
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Correcting repeated measures data to display error bars that show within-subjects differences

Although I did not check the program, your logic is indeed correct and probably the best approach. This is the approach used in superb (article found here) for the R implementation. The whole process ...
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Bootstrapping with quantiles of data instead of SD*z?

A possible alternative is to identify and form an efficient model generating a set of iid residuals. Generate a forecast using the model and then use the distribution of residuals as the basis of the ...
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Intuition for confidence intervals vs prediction intervals for linear regression

You can understand the confidence interval as an interval for the mean, which gives information about the uncertainty/variance of the model itself. A prediction interval is an interval for a single ...
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Intuition for confidence intervals vs prediction intervals for linear regression

A confidence interval is for the mean of a group of people who have the same input values for your X. If all assumptions are met, 95% of the confidence intervals you calculate will contain the true ...
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Are there possibilities to determine 95% confidence interval for right skewed data?

Usually integer data, like days, is modeled using a Poisson (or Negative Binomial) regression model, both instances of what is called a generalized linear model (GLM). $$Y \sim Poisson(\lambda)$$ $$...
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How to compute a confidence interval on the regression error?

When you form a prediction interval in regression, this is already a confidence interval for the true response value --- i.e., you use $\hat{y}_*$ and the rest of the regression information to get a ...
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Confidence interval for incidence rate if multiple events per person is possible

Looking at multiple events per subject is very common. E.g. methods for the negative binomial distribution (or negative binomial regression) are very popular and often a better than assuming a (...
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2 votes

How to calculate a permutation confidence interval?

The OP links to an abstract by Tableman, Nguyen, and Ernst (2014), who mentioned a method for permutation CIs but didn't actually describe it in their abstract. Most likely, it was the method from ...
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GAM: Confidence interval for the covariates in gratia (R)

Q1 By the convention with confint() (the generic in base R), the coverage of the interval is given by argument level, which is ...
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1 vote

Newbie question to standard deviation of paired t test

I think what you want to look at is testing for contrasts in linear models. See this link for a starting point
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Confidence Intervals for More than One Variable?

Could you use the generalised variance? Generalised variance is simply $\text{det}(\Sigma)$. Of course, we can map this to the standard error by dividing by $n = \text{sample size}$. We can illustrate ...
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Confidence in a range estimate, and +- 2sigma rule of thumb

As @whuber wrote in the comments, what I am describing is a "Tolerance Interval" (see e.g., Prediction and Tolerance Intervals). If I understand things correctly so far, one connection with ...
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3 votes

Confidence intervals for series of Covid tests

Let's begin with assuming the two tests are independent of one another (maybe run by a different lab, with reactants sourced from different companies, etc etc). Sensitivity as a probabilistic concept ...
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Obtaining formulae for Poisson confidence interval

In much the same way that the Agresti-Cooll CI for binomial $p$ approximately inverts the normal test for $H_0: p = p_0$ vs. $H_a: \ne,$ the following 95% CI for $\lambda$ approximately inverts the ...
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