Questions tagged [cluster-sample]

Cluster sampling is a sampling design in which the observation units have to be grouped together for logistical reasons (e.g., students clustered in schools or households clustered in a geographic area). Typically, cluster samples are multistage samples, so geographic areas are selected in the first stage and households in the subsequent stage.

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How to correctly estimate the ratio different of lower grain unit metric in Cluster randomized experiment?

I work on Education tech products that teachers/students would use in their learning journey. When we run experiment to test hypothesis of a feature, we need to do cluster randomization (cluster = ...
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Centering in Multilevel/ Mixed Modeling (MLM/HLM) Cross-Level Interaction Small Groups Dichotomous Variable

I am having some trouble with the literature on centering in multilevel models. I cannot seem to find a clear answer for my unique situation. I have a multilevel model with approximately 500 level 1 ...
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What happens statistically, if you create more observations by measuring more aspects of the same observational unit

Let's say that I want to measure the effect of a treatment on the performance of a firm. However my sample is very small. Let's say 10 firms. It is not possible to observe more firms. All these firms ...
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Logistic regression on correlated data (without clusters)

I would like to create logistic model using the OCA STAT Act data in R, however, since this data is a compilation of court appearances since 2020, some defendants may have appeared before court more ...
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How to calculate a confidence interval for a variable that is based on multiple samples?

Let's say there are multiple (ex: 3) coaches who are each recording the speed of the same sprinter over a constant distance multiple times (ex: 10). In order words, coach 1 will record the speed of ...
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Coding independent variable for regression based on relationship with dependent variable and reducing dimensionality

I have a table where rows are dates and columns are values of a dependent and many independent variables. I want to create regression with a number of nominal and ordinal independent variables to ...
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p-value for observing additional effects in chemical clusters by incorporating new chemicals in future

I clustered chemicals based on their structural features. Later I realized that: in some clusters, there are some chemicals (not all chemicals in the cluster) that will emit red light when shined by ...
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Can Machine Learning Models Recover "Experimental, Design and Hierarchical Structures" Within the Data?

Can Machine Learning Models Recover "Experimental, Design and Hierarchical Structures" Within the Data? At times, real world data can contain "embedded structures" - these ...
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Fixed effects in a cross-sectional data

I'm new to econometrics and need some help with my research. I'm working with research that has cross-sectional data. I have collected information about publicly-listed banks in many countries. For ...
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GEE vs Hierarchical linear regression

I am trying to choose between GEE and hierarchical linear regression for analysis of experimental vignette (2x2 factorial (0/1) design) data. Each respondent (N=160) filled in 2 vignettes, thus the ...
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Analysis of cross-sectional data with few clusters

I would like to analyze cross-sectional data of 300 patients. I would like to compare a continuous dependent variable between 7 different patient groups. The data is clustered because the patients are ...
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Data with Hierarchical Structure and Multicollinearity (E.g. ZIP Postal Codes)

I always had the following question: Can data having "naturally occurring hierarchical structure" be transformed to better make use of this hierarchical structure at different levels? To ...
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How clustering tackle autocorrelation problem in DiD estimator?

In Diff-in-Diff estimator, I did not see people using lag of outcome variable as an explanatory variable to deal with auto-correlation problem, even in some paper where the outcome variable is ...
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Calculate design effect for multistage sampling

Given that I have a multistage sampling plan which one of them involve cluster sampling, how to calculate design effect if I have margin of error, confidence interval, cluster size and sample size ...
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Do you have to simulate clustered data from a multivariate normal?

I've read a number of posts (e.g. this one and this one) in which the author simulates clustered data (some agents $n$ are allocated across clusters $c$, with errors correlated within clusters but not ...
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Clustering standard errors for difference in difference

I am running a difference in difference to examine the effect of a merger on petrol prices. I am looking to see whether the prices of company A have increased due to a merger with company B. Local ...
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Is it always better to analyze at the most granular level possible? What is the best unit of analysis in the context of hierarchically clustered data?

Let's say that I have experimental data where the level of treatment is at a higher level of aggregation than the level of observation. For example, imagine some subset of schools adopted a new ...
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Asking about clustering condition following Abadie, Wooldridge 2017

Abadie, 2017 have a paper about when we should cluster. And this paper has been summarized by McKenzie here. I used the paper of Dasgupta,2019 to link to the summarized work of McKenzie. So, in ...
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What do "random sample" and "particular population" mean in clustering?

Yesterday, from a suggestion of @Dimitriy V. Masterov here, I saw from the given link about one of the reason we can avoid clustering is You want to say something about the association between ...
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Clustering on time and instance level

I have panel-dyadic data that looks as follows: ID1 ID2 Y X90 X91 Year A B 250 23 1990 B C 113 17 1990 C A 472 90 1990 C A 100 12 1991 C B 132 18 1991 I want to estimate the effect of X on ...
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Cluster regression

I have a dataset and divided the sample into 6 groups based on 4 binary criteria (e.g. "1" for has a Chief Digital Officer and "0" otherwise). Now I want to conduct a regression of ...
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How to cluster a finite number of random variables based on their distributions?

Suppose that we have $n$ mutually independent (not i.i.d.) random variables $X_1,\dots,X_n$. We assume that these random variables can be divided into $k$ distinct groups ($k<n$), where in each ...
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Why do you only need to identify the first cluster level in svydesign(), even if you have multi level clustering?

Going through the a course on Survey Weights and it says that even though a dataset may sample using 3 clusters (like Counties, City Blocks, and households), you only need to specify the first level ...
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Statistical analysis of clustered data- but clusters in one comparison group only

I'm curious if it's still valid to use analysis techniques for clustered data when only one of the two comparison groups consists of multiple clusters. For example, the control group consists of 10 ...
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How can i calculate density of every centroid in python

i have kmeans clustered data, and cluster centroids of the kmeans. I want to calculate density of each cluster centroid and remove the cluster of the highest cluster centroid density. I did my ...
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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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If fixed effects and robust standard errors both necessary, do they have to be at the same level, and why?

I am working on an empirical paper using repeated cross-sectional data, and a reviewer has asked that we cluster our standard errors at the same level as our geographic fixed effects. Given the ...
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How to use lstm for clustered data?

I have a timeseries dataset of users with different profiles. I want to use lstm for predicting 1 day ahead of each user. My approach to the problem is first clustering users of same behaviour. And ...
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Single Observation with Some Groups. Multilevel model or other analysis?

I am having trouble determining which method to use to analyze my data. Here is the info: -575 observations nested within 292 groups -some groups only have one observation, the max number is 23 in a ...
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7 votes
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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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Stratified Sampling - Confim usage and sample size

I want to conduct a survey on a population of college students to run models on. My hope is that it will accurately represent the population. I am concerned about the sample not giving a close ...
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If you match within clusters,do you still need to use a multilevel model?

I am reviewing an article. I can't share details because the article has not been published but, briefly, the authors studied people with and without a condition and looked at long term sequealae of ...
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Algorithm to get representative sample

For a dataset I wanted to pick-out some most representative points from it. Lets say the first point could be centroid, next could be the one farthest from it in the data-set(To get variance in data) &...
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Derive an expression to estimate the total number of clusters N, with unequal cluster sample sizes m

The task in the question below is to determine the number of clusters required for a "cluster randomised crossover" design conducted over two 6-month periods, with m = subjects per cluster per period, ...
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How can I model clustered data in a regression?

I have a dataset of $N=3000$ biopsies from humans, each of which have an outcome I am trying to examine using covariates of the patient who provided the biopsy. Some biopsies from the same patient ...
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What regression model to use for both repeated measurements and cluster data (and how to do it in R)?

My research question involves looking at association between the characteristics of neighborhoods (% male, % female, income, % young people, % old people) and the participation rate in a programme (% -...
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Why is the equation for Intra-class correlation aligned with design effect of cluster sampling?

The design effect definition (link) is: $$ DEFF = 1+ (m-1)*ICC $$ It is also the relationship between the variance of estimating the mean with the cluster sampling divided by the variance if the ...
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4 votes
3 answers
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Regression model with aggregated targets

Similar as in this self-answered question, I want to ask about possible approaches for modelling data with aggregated targets, i.e. things like $$ \bar y_{j[i]} = \alpha + \beta x_i + \varepsilon_i $$...
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Is it necessary to fit cluster-level covariates for mixed models?

Suppose I have the following two generalized linear mixed models (GLMM): \begin{align*} g(\mathbb{E}[Y_{ij}|X_{ij}]) &= \beta^\intercal_1 X_{ij}^{(1)} + \beta_2^\intercal X_{i}^{(2)} + U_i &&...
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SMD meta-analysis including cluster-randomised trials: is it possible? If so, how?

Where we have cluster-adjusted results from trials (summary statistics), under what circumstances can we include them in a standardised mean difference (SMD) meta-analysis and which calculations are ...
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Balanced randomization within clusters

I was hoping someone could point me in the right direction on a randomization method. We want to randomize teachers to receive an educational intervention. The catch is that we have a number of ...
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How to know whether a random effect or a cluster effect is necessary for a mixed effect logistic regression?

I have 8 variables in my model out of which I have a group which is definitely not a fixed effect. I tried checking the random effect on the basis of the log-likehood test and it seems significant. I ...
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Analyse continuous variable between two groups/arms: cluster randomized study

I'm analysing the data for a cluster randomized study. There are 66 clusters randomly divided into two study arms: control and intervention, 33 clusters each. In total there are 2098 patients. The ...
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IPD meta-analysis: need to weight regression and population level estimates?

Using individual patient data (IPD) from various studies, do I need to weight observations in a meta-analysis? Each study used a two-stage cluster sampling design with uniform samples per cluster and ...
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6 votes
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Do GEE and GLM estimate the same coefficients?

In a GLM, the likelihood equations depend on the assumed distribution only through the mean and the variance. The likelihood equations are $$\sum_i^n (\frac{\partial \mu_i}{\partial \eta_i}) \frac{...
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Confidence intervals for survey-weighted Poisson regression in R where counts are totals of the survey weights

Forgive me if this is a very basic question. I am using a large database of healthcare encounters that uses a stratified sampling approach. Each row in the database is a sampled encounter, and has a ...
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Calculating Sample Size for Cluster Randomized Trials with Person-level or Cluster-Level Outcomes

I have been looking for a formula to calculate the estimated sample size for a two-level cluster-randomized controlled trial with cluster-level outcome data. To my reading, several authors do not make ...
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Single DV with repeated/clustered measurements of IV

I have an analytical dilemma wherein I have a single DV with multiple categorical and continuous IVs (one of which is a continuous IV that has multiple measurements across time). I'm not sure the best ...
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2 votes
1 answer
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Fixed effect and clustering with 3 dimensional data

I have a sample of banks. These vary across time, rating agency and across countries. UPDATE: I trying to capture the effect of a regulatory change (dummy variable, 0/1) on a banks credit rating. I ...
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2 votes
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Why doesn't clustering bias the standard errors in this very simple simulation?

I simulate a very simple model with one regressor and a random intercept: $$y_{ij} = \beta_0 + \beta_1x_{1,ij} + u_j + \epsilon_{ij}$$ I run model <- lm(y ~ x1) ...
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