# Questions tagged [stratification]

A sampling technique in which the population of interest is partitioned into subsets ("strata") based on characteristics known at all units before sampling.

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### Analysing stratified random sample

Let's say I am analysing an experimental design with treatment and control group which was based on random sampling design stratified on a number of covariates. When analysing the data I see two ...
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### Stratified sampling to generate random numbers (eg. for Monte-Carlo applications)

I am using a Monte-Carlo method to compute a value of interest $y$ from some input parameters $x_{i}$, that I use to draw statistical sets from simple distribution laws. In my case, for a single Monte-...
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### Confidence interval on ratio of stratified sample estimates

I have a stratified sample I have conducted in all fifty states to determine the number of people with a characteristic of interest. (Let's say, purple people.) For illustrative purposes, in New ...
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### Stratifying a multivariate dataset

I woul like to stratify a multivariate dataset in different stratas in such a way that the elements of each strata are similar. My idea is to have different groups whith the element within a group ...
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### what's the difference between stratified sampling and matching?

I am trying to find a good technique to balance data in which the minority class is about 1% of the data. As I understood, the most common practice is matching. What is the difference, though, ...
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### Fold size and stratified k-fold cross-validation dilemma

So, as far as I understand, all folds in k-fold cross-validation need to be the same size, or as close as possible. However, if one uses stratified cross-validation, each class should be represented ...
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### how to use boot package to do stratified bootstrapping?

Here's a toy data set that replicates my problem. I am interested in knowing the confidence intervals of an empirical distribution that is composed of the scores of each school at the proportion that ...
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### Optimal multivariate binning where the cut-points must be the same for all observations

I have a large data set with many discrete and continuous variables. All the variables are present in every observation. I want to explain (the log of) one continuous variable using all the other ...
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### How to control for severe medical cases using survival analysis and Cox regression?

I have a longitudinal medical record dataset. My cohort is made up of patients with a particular disease. There are no members of this cohort without this disease. Disease indications are denoted by a ...
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### Difference between Multistage Sampling and Stratified Random Sampling?

I know the question is a very elementary one, but I simply cannot understand the difference other than the fact that an SRS is a form of Multi-Stage Sampling. Can anyone provide a simple example(s) to ...
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### what type of sample is this?

I have the folowing table: according to this example, there are 40 observations distributed over 10 stores and 4 weeks of the month. Objective: to make a sample of 90%, 80%, 75% and 50% of the 40 ...
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### Benefit of scaling survey design weights

In the european social survey the design weights are scaled to the sample size (see quote and source): As with the design weights also the post-stratification weights are scaled to the sample size, ...
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### Sampling - optimal allocation for quantiles?

Say we have variable with a typical heavy tailed distribution following the Pareto principle. We divide the population into two strata (following the 80 / 20 rule) and use a stratified sampling design ...