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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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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Asymptotic variance of Metropolis-Hastings estimates on a disjoint subdivision of the state space

I'm running the Metropolis-Hastings algorithm on a state space $(E,\mathcal E)$ which can be disjointly subdivided into regions $E_1,\ldots,E_k$, $k\in\mathbb N$ ($k\approx1e5$). On $E$, I have a ...
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Stratified Sampling vs. Hand picking a “random sample”, and using Chi-Squared as justification. Dichotomous outcome methods question

Suppose I would like to evaluate "the proportion of potato farms in Idaho that use pesticides". (dichotomous yes/no outcome variable). Now let's assume I know the exact number of potato farms in Idaho,...
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66 views

Sample stratification by dependent variable in linear regression analysis

I have a theoretical question that I would like some guidance on. Is it ok to stratify a sample population by the dependent variable? Does this bias regression results? For example, I'm doing an ...
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93 views

Choosing strata in stratified log-rank test

Let's say I would like to see which factors affect the survival of patients suffering from cancer. And let's assume I have two variables: chemo ($0$ - if a patient is not treated with chemotherapy or ...
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test of difference (equivalence) between pairs of hazard ratios derived from two models

I have two stratified cox proportional hazards regression models each restricted to data on men and women, respectively. Both models have the same covariates and the data on men and women come from ...
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35 views

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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Percents of Random Samples

I have three sets $A,B,C$ of sizes $N_A=2508$, $N_B=36211$ and $N_C=2296$ respectively, containing binary values. I took 200 samples of each set to produce point estimates of the averages: $\hat p_A=0....
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Is leave-one-out cross validation (LOOCV) known to systematically overestimate error?

Let's assume that we want to build a regression model that needs to predict the temperature in a build. We start from a very simple model in which we assume that the temperature only depends on ...
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Should I use simple random sampling instead of stratified sampling when some strata have low counts?

I am designing a survey for which I would like to stratify "events" by state / province, creating $h=86$ strata for the particular dataset I'm working with. However, there are some strata with low ...
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On improving the sensitivity of controlled experiments by utilizing pre-experiment data (CUPED)

I’m currently reading “Improving the sensitivity of online controlled experiments by utilizing pre-experiment data” by Deng et al. and struggling to derive a few equations from the paper. I would ...
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Should I use stratify parameter for scikit-learn train_test_split while dealing with highly unbalanced dataset?

I have a dataset with over 200000 records. Only 400 of are positive, which makes the data highly unbalanced. I cannot collect more data. At first I trained a decision tree. I used StratifiedKFold and ...
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Experiment design: what's the difference between diff in diff and post-stratification?

what's the difference between diff in diff and post-stratification? When should we use diff in diff and when should we use post_stratification quasi experiment design?
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Variance of estimator of stratified sampling

Consider a stratified design composed of $H$ strata of size $N_h$, $h = 1, . . . ,H$. We want to estimate the population mean $μ_y$ of the characteristic $y$. Let $μ_{x,h}$ $h = 1, . . . ,H$ be ...
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How to perform inference on stratified sampling data

Let's say I'm studying a population of generic emergency calls to over the course of several months, and keeping track of the following independent variables: month (when the call happened) country (...
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1answer
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Neyman allocation and proportional allocation

Suppose that a city has 90,000 dwelling units, of which 35.000 are houses, 45,000 are apartments, and 10,000 are condominiums. We want to estimate the overall proportion (p) of households in which ...
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Stratification of sample data is lowering my accuracy?

So I've got this trainingset, it has a bunch of stuff yada yada.. Main point is that there are two target variables that only occur once in the dataset. This means I can't stratify when sampling, I ...
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Simulate confidence intervals for the absolute difference between two hazard ratios

I am examining the time to an (recurrent) event in response to different medications between men and women. I am adopting a 'within-individual' design whereby each person's time spent on- and off- the ...
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Is doing oversampling on train set and undersampling on test set correct?

I have an imbalanced dataset (95% in class 0 and 5% in class 1) and I am using machine learning for classification. The AUC(Area under ROC curve) was high (about 0.86) but AUPRC(Area under precision-...
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multilevel regression and poststratification mrp

I have some survey data. I want to calculate a regression with a stratified sample of this data. Because of the stratification, the sample size gets really small. Due to this, the standard error of ...
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1answer
540 views

Stratified Sampling on Random Forest

I am working on a project to detect crops from satellite images by prediction. To do so, I use Random Forest model. I discussed with some people about whether to give sample weights on each tree in ...
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1answer
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Determine sample size using reversed goodness of fit

I am asked to work on a specific problem in which I have to calculate certain expenditures for an industry, consisting of a population of about 400 companies. Although I already suggested to conduct a ...
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508 views

k-fold CV-scheme stratifying response and considering groups

I have the following small dataset (n~140): 1-8 samples per patient A small fraction of samples belonging to the negative class (no tumor), ~ 10-20% A larger fraction of samples belonging to the ...
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722 views

Interpreting hazard ratios in stratified models

I am unsure how to interpret hazard ratios from cox-proportional hazard models that include 1 or more stratified terms. For example, say I run a cox regression with treatment as a covariate and ...
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1answer
101 views

Odds ratio not between the two odds ratio of a stratified analysis

This is not the first time I have performed stratified analyses based on logistic regressions, but I have never before been confronted with this situation. When I test my relationship in the overall ...
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454 views

Calculating a sample size based on the target width of a confidence interval with stratification

I am reviewing a sampling design devised by a colleague and completely fail to understand it, although I am not a novice in statistics (but not a huge expert either). The said colleague is no longer ...
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61 views

random vs. stratified Cox model

What is the difference in interpretation of the effect estimates in a Cox model stratified by sex vs. with a random statement for sex? Thanks.
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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, ...