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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0answers
123 views

How to calculate the number of samples necessary to represent a population distribution?

I guess this is similar to this one but not quite the same. Consider I have a distribution that represents a population (e.g., Uniform(0,1)). I separate this interval (0,1) into three equal parts (0-1/...
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1answer
155 views

Post-stratification & quantitative variables

I'm in charge of contacting customers of a company in order to analyse their satisfaction. The problem is I contact them by phone and the people I contact (the sample) are not representative of the ...
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1answer
233 views

Interaction variables work differently when population is split

Let's say I have two predictors to predict financial risk: Gender and shopping habits. Gender has levels of "Male" and "Female", while shopping habits has "quick shopper" and "slow shopper". I am ...
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How do I address a known bias in my sample?

I have a population of interest ($N = 5000$) for which I know some demographic information. I have a sample 1500 members of that population. So I have a good sized sample, and I know exactly how it ...
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0answers
295 views

How to determine degree of freedom for a certain test of interaction?

The scenario is like this: I have a cohort with 2000 people, half of them taking DRUG, the other half not taking it. I would like to check interactions between DRUG and the other variables in the ...
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Stratified Sampling and the Central Limit Theorem

What can be said about the convergence rate of stratified sample means to a normal distribution, given different allocation schemes? Obviously, under very poor allocation, this convergence can fail (...
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3answers
2k views

Multilevel model vs. separate models for each level

What are the advantages and disadvantages of running separate models vs. multilevel modeling? More particularly, suppose a study examined patients nested within doctors' practices nested within ...
2
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1answer
309 views

Treatment effect Analysis: What is Stratification and explanation/interpretation?

In this paper by Angrist a stratification estimator is used (page 16 formula (4)) to calculate the Average Treatment Effect on the Treated (ATOT). The formula is given by: \begin{align} \widehat{ATOT}...
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34 views

Can I perform a stratified test againts a true value?

I have a study where they randomized patients into 2 groups (A and B). The primary aim is to compare group A against a fixed/ true value of 0.75. The binomial test is not stratified and cochran mantel ...
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2answers
765 views

Empirical distribution alternative

BOUNTY: The full bounty will be awarded to someone who provides a reference to any published paper which uses or mentions the estimator $\tilde{F}$ below. Motivation: This section is probably not ...
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0answers
59 views

For count data from a survey, do variance corrections for survey design imply that the Poisson distribution will not accurately model the counts?

I have categorical count data that comes from a complex survey. Each unit of analysis in the survey (household, individual, etc.)...
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1answer
207 views

Analysis of complex sample

The company where I work did a survey with a complex sample. Originally, the sample was a 2-step stratified, but due to some problems, we lost one of them (so, let's consider that the sample is ...
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1answer
1k views

clustered-stratified random sampling

i've got questions about clustered-stratified random sampling. let's say I want to do a research in narcotics. the population that I will be working with is a combination of academics, students, and ...
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2answers
10k views

When do you stratify an analysis versus including an interaction term?

I’m not very familiar with when and why you would stratify on a variable or set of variables in a regression analysis generally and would like to know what the issues are particularly in contrast to ...
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58k views

Understanding stratified cross-validation

What is the difference between stratified cross-validation and cross-validation? Wikipedia says: In stratified k-fold cross-validation, the folds are selected so that the mean response value is ...
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1answer
2k views

Fisher overall p-value vs. pairwise comparisons

I am doing comparisons on response rates across three sites. Following are the cell counts ...
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2answers
7k views

Sampling with replacement in R randomForest

The randomForest implementation does not allow sampling beyond the number of observations, even when sampling with replacement. Why is this? Works fine: ...
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2answers
1k views

Beta coefficients from stratified analysis when there are covariates?

Suppose I have a regression model shown below Model 1: $$ Y = \beta_0^\ + \beta_1SEX\ + \beta_2ALCOHOL\ + \beta_3SEX*ALCOHOL\ $$ The predictors I am interested in are SEX (binary: 0 female, 1 male) ...
4
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1answer
128 views

What are the optimizations or goals to consider when using stratified sampling?

In stratified sampling, what are the optimization considerations? For example, the sample size per stratum could be defined with proportional allocation as $n_h=n\frac{N_h}{N}$, where $N_h$ is the ...
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1answer
1k views

Possible catch 22 with Neyman's optimal allocation

I am using stratified sampling and neyman's optimal allocation to compute the best sample size for each stratum. neyman's optimal allocation is given by the formula, $$n_h = n \frac{N_h * S_h}{\sum_i ...
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2answers
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Why is random assignment important in stratified sampling?

Background I raised this question because of an argument I am having with a question from user697473 here. The title of his question is "Formal definiton of random assignment." In the post he ...
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1answer
2k views

Stratified classification with random forests (or another classifier)

So, I've got a matrix of about 60 x 1000. I'm looking at it as 60 objects with 1000 features; the 60 objects are grouped into 3 classes (a,b,c). 20 objects in each class, and we know the true ...
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2answers
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What is the name of this type of stratifed sampling?

I am not sure what this specific type is called so I will describe what I did in Excel. This was employee data: Sample size is prescribed. Example: n = 100 (though the population N = 10000) Sort ...
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1answer
271 views

How to efficiently expand a simple random sample after population growth?

I have a simple random sample (SRS) $S$ of size $n$ drawn from a population $D_1$ containing $N_1$ members. A new set $D_2$ with $N_2$ members is added to the population. I would like to create a ...
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3answers
203 views

Derive househould weights from a uniformly distributed person sample

The Swiss Public-Use Sample of the national census is a 5% sample drawn from the entire census survey. According to the documentation, the persons are sampled uniformly without replacement. Persons ...
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2answers
5k views

Remove duplicates from training set for classification

Let us say I have a bunch of rows for a classification problem: $$X_1, ... X_N, Y$$ Where $X_1, ..., X_N$ are the features/predictors and $Y$ is the class the row’s feature combination belongs to. ...
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1answer
9k views

Stratified sampling with multiple variables?

I don't know much about stats so I'm looking for a starting point here. Any resources or insights would be helpful. I'm conducting an e-learning experiment, in which students watch videos and then ...
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1answer
964 views

Stratified Cox model

I am working on fitting a Cox model to predict. But several predictors violated the proportional hazards assumption. I am gonna to do stratified Cox model to adjust them. But the results of stratified ...
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1answer
5k views

Bootstrapping stratified sample that is weighted to population - reweighting during the bootstrap?

I'm using R to provide bootstrap (percentile and t methods) of estimated population totals, using data from a complex survey. It is a stratified survey of tourists expenditure that is weighted to ...
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2answers
705 views

When using stratified randomization in a RCT, how many envelopes per stratum should be prepared?

If one considers a hypothetical RCT, say a total sample size of 300, separated into three strata based on surgical procedure (open surgery, closed surgery, or combined procedure). Blocking in groups ...
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2answers
1k views

Stratified sampling question

Suppose that I am conducting a questionnaire study that is trying to measure level of awareness of subjects about a programming language and find the relation of those level of awareness to working ...
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3answers
3k views

Simple post-stratification weights in R

I just got my hands on the ANES (American National Election Studies) 2008 data set, and would like to do some simple analysis in R. However, I've never worked with this complex of a data set before ...