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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4
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1answer
124 views

Downsides of stratified randomization in experimental design

When sample sizes are too small to trust that the usual asymptotics will guarantee good balance across experimental groups on known confounders, a common approach is stratified or blocked ...
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1answer
649 views

How to avoid overfitting in stratified k-fold cross validation methods for classification?

I'm using stratified 10-fold CV on my data set that is imbalanced. I've read in articles that this method is useful for such data set. But I'm not sure if I'm using this method as well. In each fold, ...
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171 views

dataset shift and adjustment in glmnet

I have two sets of data A and F; In each datasets, I have two types of data point, say, 0 and 1 and the goal is to make a classifier. One strategy is training/fitting the model, using one dataset, ...
2
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1answer
89 views

Small Random Samples vs one Random Sample (Stratified)

Backdrop - I will be doing stratified random sampling from a data that is about 100 million events. Distribution of this original data is extreme long tail (1% of objects contribute to 95% of events). ...
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1answer
2k views

How to weight data according to multiple variables

I have two datasets. Dataset A is considered the population. It has 7 variables with different number of classes / breaks for each. Dataset B is the dataset I want to make look like Dataset A in ...
3
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1answer
657 views

Reweighting sample to reflect census?

I'm working on a revision of a manuscript. I have a longitudinal cohort of adolescents that were followed throughout junior high school. One of the reviewers considers the attrition to be considerable,...
3
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1answer
832 views

Using strata instead of stratifying groups separately?

Can someone help me understand what strata(groups) does when it is used as a covariate? I am used to seeing stratified models where each level is run as a separate model, so that you can get ...
2
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2answers
227 views

Why class stratified sampling is not compatible for naïve bayesian modeling, if sampling is used?

I read a book recently and it mentioned related to prior probability of naïve bayesian: "Since the probability of an outcome is calculated from the data set, it is important that the data set used ...
2
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1answer
3k views

Standard Error for Sum

I am designing an algorithm for a stratified sampling on a population and then I want to find out what is the error bound for 95% confidence interval, for different sample statistic such as sum of the ...
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1answer
625 views

Propensity score stratification: standard errors and p-values

While there are many tutorials on how to perform propensity score stratification, I was unable to find any example that showed the calculation of standard errors and p-values for the final estimate. ...
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0answers
77 views

What does it mean if the ROC scores are quite different when using the Stratified K fold with and without shuffling?

I'm currently building a random forest classification and trying to measure the model performance by the [mean ROC area]. With the same data set: When I use cross_validation.StratifiedKFold(y, ...
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1answer
741 views

Two sample tests for stratified randomization

I have to test the difference between two samples which were selected via stratified randomization. The problem is that the samples are not independent due to randomization was stratified. How should ...
2
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0answers
252 views

Correlation with stratified data structure

I have a dataset with two stratas, the first level is called block, which represents the census block. the second level is two predetermined subgroups in each blocks, each subgroup contains several ...
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529 views

How to estimate survey data at cluster level in a stratified clustering survey design?

While estimating from the survey data involving stratification & clustering survey design and using survey package of r, is it possible to estimate at the cluster level? For eg; for following ...
13
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1answer
1k views

Does fitting Cox-model with strata and strata-covariate interaction differ from fitting two Cox models?

In Regression Modeling Strategies by Harrell (second edition) there is a section (S. 20.1.7) discussing Cox models including an interaction between a covariate whose main effect on survival we want to ...
2
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2answers
676 views

Different “end of study” times for different cohorts - Cox PH model in survival analysis

I have a dataset with 4 cohorts of about the same size (~700 people each). I'm trying to apply a Cox PH model using the time needed to pass a very difficult exam as my "time" variable. The cohorts ...
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65 views

Stratum on subset of data: drop if too small?

We have genotype data for ~20000 samples with 4 principal components and 10 strata - study centres. Formula for an example analysis would be: ...
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0answers
2k views

Calculating needed sample size for two stage stratified cluster sample

We want to carry out a survey to assess perceptions of quality and access to medical education of last year students. Based on our research, we have decided that a two stage stratified cluster sample ...
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2answers
3k views

Using post-stratification weights in R survey package

I am analyzing a dataset that has a variable for post-stratification weights. As this is a complex survey, the plan is to use the R survey package. I have been ...
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1answer
29 views

What effect does the weight function have in the stratified population mean formula?

The stratified population mean formula is $\bar{X}=\sum_{h=1}^HW_h\bar{X}_h$, where $W_h=\frac{N_h}{N}$ is called a weight function. Can someone explain intuitively what affect this weight function ...
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1answer
93 views

Data stratification for long-tailed distributions

I'm encountering a few problems successfully stratifying a dataset that is long-tailed to the right. In my research, I came across this excellent response: Sampling from a long tailed distribution ...
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1answer
678 views

Post stratification weights and the survey package in R

I have survey data that needs to be weighted, and to help me with this task, I have access to the full joint distributions of the variables I want to use. As I understand it, I should use the ...
3
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0answers
45 views

Can unintentional sample stratification be problematic?

An example of what I mean: I have a certain essay from all students at a university. I take a 1% random sample (not stratified) and run some time consuming computational analysis on each essay ...
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3answers
623 views

Calculating Sample Size for Non-Inferiority Test in Cox Proportional Hazards Regression With Stratification

I have a binary predictor, X, in a Cox proportional hazards regression model, and I want to show that it is NOT a significant predictor. In other words, I want to show that there is not a significant ...
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36 views

Ideas for sampling design

I have a data base of schools per district and the number of teachers per school. I want to select a sample where between 1 an 10 schools are selected in each district. Once a school is selected, the ...
3
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1answer
3k views

How to conduct Cox PH stratisified by matched pair in R

I am wanting to calculate hazard ratio in a matched cohort design. For such I am using the coxph() function in R. But I have been recommended to stratify by matched ...
7
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1answer
1k views

Is stratified meta-analysis more or less objective than meta-regression?

Reviewer asked me why I use meta-regression as a way how to deal with heterogeneity among effect sizes instead of conducting stratified meta-analysis. I tried to google "stratified meta-analysis" and ...
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1answer
509 views

Ignore strata in external validation of stratified Cox prop hazards model?

I've fit a stratified Cox proportional hazards model to some survival data, where I've stratified by a potential confounder which is the batch the data comes from (there are three batches). Now, I'd ...
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1answer
549 views

Deriving the formula for the mean of a stratified sample

The formula for the mean of a stratified sample $\bar Y_s$ is: $$\bar Y_s = \frac 1 N \sum_i N_i \bar Y_i$$ where $N$ is the sample size for all strata, and $N_i$ and $Y_i$ are the sample size and ...
27
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2answers
15k views

Why use stratified cross validation? Why does this not damage variance related benefit?

I've been told that is beneficial to use stratified cross validation especially when response classes are unbalanced. If one purpose of cross-validation is to help account for the randomness of our ...
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1answer
57 views

which statistical sampling technique to employ to have a representative sample

There is kwashiorkor outbreak in my community Abeng (a city in Africa). The community is in sections A to F and it heterogeneous in nature.
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2answers
395 views

How to partition a training-set when I have a big class imbalance?

In my actual data class A has 90%, class B has 9% and class C has 1% (numbers are made up for sake of simplicity). Now I want to prepare a training set for my classifier (I plan to use Vowpal Wabbit). ...
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2answers
1k views

Stratified or multi-stage sampling?

I just started volunteering with a small organization that wants to estimate the average and total number environmental trouble spots in a large US city. They have a clear definition of an ...
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0answers
96 views

How would I factor study design into relative risk?

I'm comparing various conditions versus some disease for a large stratified/clustered dataset which purports to account for the entire population after weighting -- hence the use of RR instead of OR. ...
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0answers
367 views

Stratified random sampling and its distribution

I'm learning stratified random sampling and I'm having hard time to solve this problem. consider the following population of six units: ...
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1answer
2k views

Individual and overall RMSE for multivariate data

I have a dataset which contains missing values, and I'm using imputation packages (Rs mi and ...
5
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1answer
2k views

Confidence interval for a proportion estimated through stratified sampling

When estimating the confidence interval for a binomial proportion $p$, with $\hat{p}$ near 0 or 1, one has to use something other than the Wald interval to get a reasonable estimate (see for instance ...
7
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1answer
2k views

Machine learning with weighted / complex survey data

I have worked a lot with various nationally representative data. These data sources have a complex survey design, so the analysis requires the specification of stratification and weight variables. ...
4
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0answers
632 views

Stratified Cross-Validation with Collaborative Filtering

My dataset consists of binary preferences ($0$ or $1$) given by users on items like this: User-ID | Item-ID | Preference If a user has not given a preference to an item, then it is not in the ...
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0answers
44 views

Accounting for noncoverage in survey

[I'm a stats noob, so please correct if I am going wrong somewhere!] We run a survey of our customers based on certain events or touchpoints. The responses vary significantly by these touchpoints, so ...
2
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0answers
117 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/...
6
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1answer
153 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 ...
2
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1answer
232 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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0answers
56 views

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 ...
2
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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 ...
2
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0answers
290 views

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
303 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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0answers
33 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
754 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 ...