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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Static risk prediction models and years-to-live stratification

A known paradox is the fact that although the absolute risk for developing a disease may rise with age, the conditional probability for every person to develop a disease, given that he hasn't ...
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When to use fixed effects or multi level models in regression?

Suppose you run an experiment where the treatment is Gatorade and the outcome is one-mile runtime. You’ve stratified on variables such as sex, height and weight so they’re well randomized and have no ...
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In SAS what is the difference of including treatment variable in model and using the strata statement for treatment variable?

Im building a Cox Regression in SAS. My code looks like this: ...
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Stratified SRS vs. probability-proportional-to-size (PPS) sampling - what's the difference?

If my understanding is correct, the key difference is that: In stratified SRS you intentionally draw $N_h$ samples from each of your $k$ strata ($h = 1...k$, $\sum_{1}^{k}{N_h} = N$) and are ...
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Regression on a Stratified Sample [duplicate]

I am doing some regression analysis on a stratified sample where the stratification variable is the dependent variable. Do I need to adjust the regression or the results to account for the ...
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Validation of a stratified randomization plan

In my team, we are conducting clinical trials using stratified block randomization with random block size. Depending on the user, the randomization list will be generated using custom SAS macros or R ...
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Understanding stratified approximate randomization test

I have been looking at a code base that can calculate evaluation metrics. It implements bootstrap resampling to calculate confidence intervals, and also uses stratified approximate randomization for ...
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Measuring treatment effect when the dosage is not under your control

I'm running an ab test for an on-demand service where one group receives compensation in response to poor service, while the other group does not. The hypothesis is that "compensating for poor ...
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Stratified-Extended Cox regression modeling to deal with survival data with time-varying covariates

I'm working on Cox regression in my PhD research and I would like to know some references about applying the stratified-extended cox regression model on a real life data. I'm interested about ...
Youcef Bouzir's user avatar
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How should we stratify the space for Metropolis-Hastings?

Say I'm running Metropolis-Hastings with target density $p$. What I would like to do is divide the space $E$, on which $p$ is defined, into a disjoint union $E=\bigcup_iE_i$ and run a separate ...
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How to deal with survival analysis when censoring time depends on a covariate

I'm performing survival analysis on time to drop out of a certain program. However, the censoring of each case depends heavily on the length of the program. For example, some programs only last 3 ...
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When monitoring a sample, how to gauge when a substratum significantly exceeds sample size estimates and should therefore have its rates adjusted?

I'm in charge of a year-long, stratified sample where the population is estimated based on previous years but which is also quite dynamic, changing in unpredicted ways every year (furthermore, past ...
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How to combine strata in bootstrap resampling to produce a confidence interval for the population statistic?

Let's I have $k$ strata, each with resamples $\mathcal{D_i}$ resamples where $i = 1 ... k$ Each has some confidence interval $[\hat{\theta_i} - \theta^{\star}_{i, \alpha/2}, \hat{\theta} - \theta^{\...
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How to combine a two strata, where one is fully sampled and the other partially sampled, and the sampling statistic is highly skewed

I am estimating the mean of a highly skewed sampling distribution. I have a full sample of 80% of the population. I have a small partial sample of 20%. I'm using the bootstrap to estimate the ...
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What is "information leak from test to train" ? Is stratification by target a leak?

It's common practice to do procedures such as standardization and even missing value imputation (commonly based on some means) after train/test split - otherwise it is treated as information leak from ...
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Stratified sampling for household dataset. Multiple targets or single target?

I am new in stratified sampling. I have a regression task to analyse the relationship between income, household size and expenditure, using python. Both income and expenditure are continuous variables,...
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Which of the variables appear to be effect modifiers. When stratifying by each variable, which seem to indicate the presence of interaction?

The following graph displays five pairs of stratified odds ratios (not from the same study) with 95% confidence intervals. For this plot, assume the confidence intervals indicate whether the stratum-...
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Relative Error when using an erroneous neyman allocation

I'm having a lot of issues trying to derive an equation for the relative error in the following problem. Someone has used the following incorrect formula to perform Neyman allocation $n_{h,e}=n\frac{...
Jack Gorman's user avatar
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Is Neyman allocation sampling the best approach?

I have a data set of the 2020 value of 15,000 unique objects. The value is right skewed. I have to draw a sample of 500 unique objects based on the 2020 value (range = $1-40,000). The present value of ...
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Randomised controlled trial stratified by site - inclusion of site as fixed effects or clustered standard errors?

I have a 2-arm RCT which is stratified by two factors: Site (2 sites) Disease presence (presence; absence) The analysis of the primary outcome (binary) will use a log-binomial GLM to generate the RR ...
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Disproportionate stratified sampling that follows proportional trend?

I'm conducting a study across four counties to determine which of four different methods is most effective in detecting nutria. 60 sites will be randomly selected within a 5-meter buffer of any open ...
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Is it appropriate to pre-stratify and post-stratify along different delineations of the same variables in a single survey?

I am working in the context of opt-in, web-based surveys. Often the desire is for accurate population estimates, and often at a country-wide level. The standard approach at this organization is to ...
spathartic's user avatar
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How can I show probability of selection change when adding stratification to a survey design

I have a survey that uses a stratified sampling approach with optimal allocation. The team conducting the survey has asked that we make two changes: Subdivide one of the strata into smaller pieces. ...
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Why can stratified sampling to testing/training sets on strata that contain less than 10% of the entire dataset be statistically risky?

I'm trying to split my data into a testing and a training set. There are lots of variables that I want to ensure are well represented in both the training and testing sets (say, 15 covariates). But ...
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Regression Analysis for Stratified Random Sampling

I have some data that was found using a stratified random sampling procedure. We used this process to directly sample from the entire population and record Metrics that we were interested in. From my ...
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Sampling Methodology for QA/QC Sampling

I need a bit of help / nudge in the right direction. I am currently wrapping up my MS in Applied Statistics and have learned a ton about the subject. Recently I was approached by one of our business ...
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Stratified sampling where observed values vary with strata inclusion

Problem set-up: Let's say I make $n$ observations of a numerical-scale variable, $x$, where each observation can be cross-classified into $L$ strata. Each observation may belong to anywhere from 1 to $...
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Difference between stratifying and categorizing a variable?

What's the difference between stratifying a variable within a model vs making a category variable out of it? Does the difference lie in that stratification affects how all the other variables are ...
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Are stratified variables still significant?

...
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Grouped stratified train-val-test split for a multilabel dataset

I was wondering if there is a fast heuristic algorithm for performing grouped stratified dataset split on a multilabel dataset. Question originally posted on Data Science stackexcahnge here. ...
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Stratified cox reg analysis

I am trying to make a stratified cox reg analysis in R studio, where I want to see the differences in exposure to MT divided by gender. I used the following code: ...
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pre-stratification(blocking) vs post-stratification

$Q:$ When should I consider pre-stratification(blocking) vs post-stratification? From experiments, I would certainly consider pre-stratification but post-stratification seems to homogenize the sample ...
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Strata Sample Sizes and Stratified Sampling

I am trying to conduct a research study on the local population of homeless individuals in my county. But, before I can detail my study, it would be helpful to provide some context. Context: It is ...
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How do you calculate the total sample size in stratified sampling?

I know that we can allocate observations from the total sample to each strata either using proportional allocation ($n_{h}/N_{h} = n/N$) or optimal allocation: $$n_{h} = \left [ \frac{\frac{N_{h}S_{h}}...
NoLifeKing's user avatar
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Inconsistent handling of lonely PSUs in R's `survey` package?

There appears to be some inconsistent handling of lonely PSUs in R's survey package when calling svyglm on a subset of ...
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Optimal sampling strategy when only marginal group sizes are known

I seems to me that this cannot be such an uncommon situation but I find I cannot come up with the answer myself and I also cannot come up with the correct search terms to find it, either here on Cross ...
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2 answers
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Train test split based on statistics

I would like to know if there is a method of splitting that is not random but based on the distribution of the train and test data samples feauture values. Currently I am splitting randomly but ...
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Age and sex standardised incidence rates

If I were to compute age-sex standardised incidence rates based on a simple random sample of a nationwide household survey on hearing loss. Noting that this a sample not the total population, so the ...
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1 answer
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Computing standard errors when using stratified sampling

I am trying to understand the following formula for the standard error of the population mean as estimated through stratified sampling. On the CRAN site, the formula given is $$ S_{\bar{x}_{\textit{...
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Causal inference, stratification to mitigate confounders in continuous variables?

Handling confounders in continuous variables In Statistical Rethinking, the author shows that in different situations, a confounder (fork, pipe, collider, descendent) will induce spurious correlations....
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Should I keep discovery and validation samples separated also for subanalysis and stratification?

I am conducting an analysis on RNAseq data on two populations sampled from different geographical regions. I used population A as discovery (about 120 samples and 150 matched controls) and population ...
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K-fold Stratified cross validation on a dataset with examples of variable length

I have a dataset of audio recording of variable length with large std which are heavily imbalanced in terms of total duration per class. So in stratified k-fold cross validation I would like to main ...
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How to update survey weights after fixing strata membership/assignments?

Imagine we conduct a survey using stratified sampling, and after the survey closes, we find out that we had misclassified some of the respondents. They actually belong to different strata than we had ...
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1 vote
1 answer
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Estimating a population total from a stratified simple random sample

I have a stratified population. I want to estimate a population total $T$ from a stratified simple random sample. I have two strategies: I compute $\displaystyle T=\sum_h N_h\bar x_h$ where $x_h$ is ...
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1 answer
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Subclassification on a propensity and prognostic score grid with k × k subclasses, using R MatchIt

I would like to perform a joint subclassification of some data on the propensity and prognostic scores as described in this paper "On the joint use of propensity and prognostic scores in ...
John Preston's user avatar
1 vote
1 answer
138 views

Cox PH controlling for multiple events

I'm working on a cox proportional hazard analysis in R using the survival package. I´m analysing covariate effects on fish movement within a study area. The study area is divided into two zones ("...
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Choosing an equal number of samples from each strata - what is this called?

Suppose I have a highly skewed distribution and a proxy measurement. I use this proxy measurement to bin the samples of this distribution into different "strata". I then take N samples from ...
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When having non-proportional hazards, should I use stratified Cox by time or Logrank tests within periods?

My data have non-proportional hazards with clear separation. Should I handle it via stratified Cox regression or using separate Log-rank test within subsets? I will use R only to illustrate. I want to ...
Aronovsky's user avatar
2 votes
1 answer
135 views

When computing period-specific hazard ratio using Cox, should I add variable:strata or full variable * strata?

Let's asusme I want to calculate separate hazards ratio in two periods, split like below. ...
Aronovsky's user avatar
1 vote
1 answer
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How to resample members from the population who didn't respond after the survey?

I have used stratified random sampling on population to generate the sample. Now the issue is if after the survey is conducted some of the members in the sample ...
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