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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Stratification McNemar Test in R

I have categorical data before and after a condition (paired data) about preferences (yes/no) and I have other variables such as sociodemographic values (sex, ethnicity, etc). What I need to know if ...
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Am I correct in my understanding adjustment for covariate vs. stratyfing by it in the Cox regression?

I'm trying to understand the difference in a Cox model between adding a single categorical covariate like sex = {male, female} and doing stratification by it. I'm not saying about such trivial thing ...
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Leave-one-out cross-validation and stratified bootstrapping together

I had asked a related question related here I was told that I am using a kind of bootstrapping. I didn't realise it then. Based on the responses, I tried to understand what exactly was going on. I ...
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Why use a stratified log-rank test if we balance over strata anyway?

When comparing survival data over time, we can use the log-rank test. An extension of this is the stratified log-rank test, which adjusts for variables. Let's say we wanted to adjust for the effect of ...
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If I want to control for race in SEM, should I include race in the model, or should I run the model multiple times with 1 race category at a time?

I am running a SEM model. There is 1 independent variable, 1 mediator, and 2 dependent variables. All variables are continuous. I want to control for race (White, Black, Latino). To control for race, ...
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In a stratified RCT, should strata be combined if a too small sample size is attained in randomization?

My question refers to a situation where the number of participants in some strata is unexpectedly low. Should randomization proceed in the same way as declared in the Protocol, i.e. by performing ...
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Relative increase of variance for stratified simple random sample

My attempts: I know that for a stratified simple random sample, the variance of $\hat{t}_{y,st}$ is $V_p(\hat{t}_{y,st})= \sum_{h=1}^L N_h^2(1-\frac{n_h}{N_h})\frac{S_h^2}{n_h}$ where $S_h^2$ is the ...
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Is there a need to account for confounders if crude association is not significant?

Background: Swallowing exercises are prescribed to head and neck cancer patients during radiotherapy to prevent swallowing impairment Aim: Determine impact of swallowing exercise compliance on ...
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How to weight samples in a subsample of a stratified sample?

Suppose I'm first interested in computing the percentage of people in a certain town with brown eyes. However, due to some constraints I end up with the following stratified sampling set up: $$N = ...
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Computing estimates for segments of a sample

Suppose I want to estimate the average body weight of people in a population. I use a stratified sample of 50% men and 50% women and compute the desired metric. Next, I want to compute the average ...
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Post-stratification: What are the possibilities if your data has too many factor levels to run?

The example below is a simplified version of my actual problem and data. I have a sample of n=2000 observations of individuals surveyed throughout a country in a certain year. So my actual data is not ...
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How to do augmentation and k-fold cross validation?

I am solving one NLP problem which by default gave me train and test data. Test data has no labels while train has. Now I split train dataset into train(I will call this as updated train dataset) data ...
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Would very small stratum be a problem for ANCOVA model?

I know that for logistic regression, if you get an empty cell, the model may not run at all. How about continuous outcome? If one of the categorical predictors has very small stratum, would there be a ...
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Determine stratified sample size $n$ with confidence level 95%, if required $SE $ of the estimated mean is given

I need to calculate sample size $n$, so that $SE$ of the mean would be 4 points. There are $55$ units in total in the $I$ group. $N_2 = 80$ in the $II$ group and $N_3=65$ in the $III$ group. The ...
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How to show that $n_h $ is proportional to $\left(\frac{W_h^2S_h^2}{t_h}\right)^{\frac{3}{2}}$?

If cost function is given in the form $C = c_0 + \sum t_h\sqrt{n_h} $, where $c_0$ and $t_h$ are known ($t_h$ - transport costs to survey one element in a particular strata). Show that minimising $D(\...
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How to calculate and compare ML models Recall estimators from stratified sample?

Let's say that I have 2 machine learning models for a disease (binary) classification task. I would like to estimate Recall for both models and compare it (show statistically that for example Recall ...
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Confidence Interval around a single strata's proportion in a stratified random sample?

I am conducting a stratified random sample of properties in 10 cities of a binary attribute (has fence yes or no). This is using remote sensing so no response rate, it's me inspecting images of ...
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Stratified shuffle for normally distributed target variable

When splitting data for a classification problem one is advised to use stratified shuffling in case the target variable is skewed toward a certain class. Indeed, Sklearn has a function for that. ...
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What is the optimal sampling split for stratified sampling?

Suppose we have a population split into two strata of interest and we want to estimate the mean of some quantity of interest pertaining to the population. Denote the quantities of interest for the ...
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Conducting a Stratified Random Sample (Statewide Poll)

I am interested (in theory) in conducting a stratified random sample of $n$ registered voters from a state which has 150 counties. If I make all 150 counties my strata, must I conduct a random sample (...
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How to determine sample weights, when the prevalence in the population is based on percentages

The central question is: How to do I determine the weights, when prevalence in the population is expressed as percentages? I have posted this related question on Stack Overflow: According to the ...
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How to group countries with similar age distributions?

How can I group the world's 200-odd countries into (say) ten groups, with each group's countries having 'similar' age distributions? I want to compare COVID-19 fatality rates across countries. But the ...
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Can I read into the coeff or the effect size of independent variables in a mixed-effects logistic regression model if I did stratified sampling?

I am building a mixed-effects logistic regression model. I want to understand the impact of certain predictors. I am reading into the coefficients and the effect size (wald's statistic). One of the ...
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Determine sample size for each cluster

Suppose I have a large population and I want to test if installing a new special light bulb can reduce energy consumption. Since I have a large population, I'll have people that usually consume high ...
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Creating stratified subsamples from a sample (repeated observations) - Post stratification

I have a random sample of individuals in a country (without knowing in which province they live). From this sample I want to make stratified random samples on the provincial level (let's assume there ...
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How is stratified sampling better than sampling equally from all classes while crossvalidating?

I can see that stratified sampling helps in maintaining the same class distribution in the training set as in the original dataset. However, my understanding is that ideally, the model should be ...
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crossvalidation “balancing” for regression problems

Classification problems can exhibit a strong label imbalance in the given dataset. This can be overcome by subsampling certain class weight attributed weights, which allow for balancing the label ...
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What is a non-random k-fold cross-validation that is not aimed at representativeness?

I am working on a project where my dataset is structured as follows: for each observation, I have a concept translated in five languages, and a measure of word concreteness. So something like: ...
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Ex-post grouping blocks, when analyzing blocked randomization experiment, to avoid $N_b=1$ blocks

In an experiment I conducted, randomization was stratified geographically and then blocked by the baseline outcome variable, $x$. That is, within each strata, $s$, I grouped observations into blocks, $...
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Proportional allocation vs Neyman Allocation [duplicate]

I am trying to figure out how to use both allocations for an assignment and I am having a hard time figuring it out. More importantly, can someone explain how to use proportional allocation to me by ...
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Can oversampling be moved outside stratified k-fold CV?

In a binary classification task, I am using imbalanced-learn's implementation of SMOTENC to oversample the positive class of a very imbalanced dataset. The total number of examples is very high, so ...
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Why adjusting for randomization stratification factors in the model improves the precision of estimators for treatment effect?

I assume you will already get balanced treatment assignment within the randomization strata. Why would we still gain improvement in precision by adjusting for these factors in the model? Does not ...
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Age stratified analysis in R

I am working on a project for which I need to do age stratified analysis for age of onset, age at last visit to the hospital and age at death. Our collaborator wants me to create an "Age ...
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One random sample Mean or 30 Random samples Mean

I have 30m records and i want to do a random stratified sample to estimate the mean based on predefined strata. Should i estimate the mean while taking 1 random (n=500) sample or to sample lets say 30 ...
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Difference between stratification and subset

This may be a duplicate question asked differently, I am curious to know the difference between performing an analysis by stratification on a variable and by subsetting the dataset based on that ...
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Stratified sampling

I am learning about stratified sampling, and I have the following question: can stratified sampling achieve more precision than SRS if data is plentiful and the samples are big enough? For example, it ...
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Stratify Cox Proportional Hazard Model on continuous variable

I have a question regarding Cox proportional hazard models. I've been working with data with some time-varying variables and some that are fixed over time. In total 79 units are surveyed giving around ...
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When splitting a dataset into train/dev/test sets, how perform stratified splits on some labels but exclusion split on others?

Suppose I have a dataset of 1000 samples with label classes A, B or C that I want to split into train/dev/test sets in a stratified fashion. However, each sample has an origin metadata (o1, o2, o3, ......
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How do I calculate the survey sample size using stratified sampling?

Lets say I plan to do a survey of individuals aged 40-69 years old in 5 residential complexes. It is a general social survey, and is intended to survey attitudes towards a new cultural centre that ...
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How to set break values for a cross-basis function in R's DLNM package?

I am using distributed lag non-linear model in R for a time series data. I am forming a crossbasis matrix using following script: ...
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Stratified Sampling Total Statum

I wish to find the number of total population by each specification. I have the following results: \begin{array}{|c|c|} class & n_h \\\hline Positive & 5872 \\\hline Neutral & 6771 \\\...
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Stratified logistic regression with log link

I noticed the other day that I can mimic a stratified logistic regression using a meta-analytic approach at least when there is only one stratification variable with two different values. This is the ...
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Are the differences between sampling clusters and sampling strata, conceptual, methodological, neither or both?

I am fuzzy on the distinctions between sampling strata and sampling clusters. Both seem to aim at designs aiming at creating useful estimates of between/within group (strata, cluster) variation, and ...
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Long-tailed predictors for likelihood prediction

I have a set of long-tailed predictors and a binary target variable. The long-tailed predictors have also 0 values. The data-set is imbalanced with about 5% of positive class samples. I would like to ...
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what is the best sampling procedure to use? (stratified)

all, i am a little confused on what sampling method to use. i am doing a classification problem where i am trying to classify a person as having cancer or not. there is apparently huge variance in ...
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Main options on how to deal with imbalanced data

As far as I can tell, broadly speaking, there are three ways of dealing with binary imbalanced datasets: Option 1: Create k-fold Cross-Validation samples randomly (or even better create k-fold ...
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Should I maximize the number of respondent (total or per strata), or the similarity between the sample and the general population?

I want to conduct a market research survey. I want to interpret results for both the general population, which is very large, and also for age and household income subgroups. With the limited budget ...
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How to explain that leave-one-out cross-validation doesn't need stratification in the context of classification?

Stratification is usually defined as training data and testing data having the same distribution of class values. In leave-one-out cross-validation, each fold only has 1 instance. I know that it's ...
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Distribution of the grand mean (mean of means), and case of stratified sampling

I am having some trouble while estimating the distribution of the mean of means, according to the type of sampling. Basically, I sampled N=1000 sets of n=100 random numbers distributed as an uniform ...
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Post Stratification & Calibration? - Adding weight's - CALMAR

Let's suppose that I want to compare the average spending of both groups and I have two groups with 2 features in each one: Each client is unique and CityCode has only 2 groups CA and CB and AgeCode ...

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