Questions tagged [pooling]

Pooling, eg for variance, is used when several groups or populations are assumed to have a common property (a common parameter value) and the information from all the groups or populations are used together to estimate that common property.

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9 views

Can pooled standard deviation be used to determine sample size?

I would like to use Minitab statistical software to determine a minimum sample size for precision (repeatability) testing. From casual observation, we know our allowable error is much wider than the ...
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Are there special techniques to combine estimates and standard errors from a complex discrete-event simulation?

My discrete-event simulation works as follows: A sample is drawn from a simulated population The simulation is run a few times for that sample Each run produces k estimates and their corresponding ...
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tf sumpooling layer 1d vs 2d

I am currently working on a paper by Sturm et al. (2016) published in the Journal of Neuroscience trying to replicate their results using python and TensorFlow, Keras libraries. I have strong doubts ...
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Multinomial logistic regression with pooled data (year dummy?)

I am trying to run a multinomial logistic regression with the dependent variable of three categories (non-user, basic user and advanced user). I have data from 2015 to 2018 with many socio-demographic ...
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Hypothesis testing - Difference proportions: Pooled vs Unpooled for one-tailed tests

Problem 2 of the Stattrek tutorial (https://stattrek.com/hypothesis-test/difference-in-proportions.aspx?Tutorial=AP) tries to determine whether a drug is more effective for women than for men. They ...
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Creating Models For Pooled vs Panel Data

I have a data set that contains data for 10 of the same stocks for a period of 10 years. This would be considered panel data. I have read that I can not use OLS on panel data because observations are ...
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Does max-pooling increase the receptive field? [duplicate]

I'm new in deep learning. when applying convolution on the image , the receptive field is increased but when applying max pooling on the image, I don't know the receptive field is increasing or keep ...
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In convolutional neural networks, are max-pooling layers used to reduce the number of parameters?

I was asked this question in an exam. I answered "Yes" but the right answer was supposed to be "No". I guess there is no debate that max-pooling layers do reduce the number of parameters in the fully ...
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35 views

Gelman multilevel regression analysis, understanding of formula for partial pooling estimates

I'm looking through Gelmans data analysis using regression and multilevel models and want to know whether I understand the definition on page 253 (12.1) which is as follows $$ \hat{\alpha}_j^{...
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20 views

pooling variable depth samplewise / are there any importantce to take into account?

My purpose is to apply pooling strategy (max/average) with a variable depth length of the samples in a batch. My question is whether is there something what I should take into account. Does it ...
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Combining F-values from multiple imputation datasets using R [duplicate]

I am currently working on pooling F- and p-values from the ANOVA tables in SPSS regression output. While I tried using various aspects miceadds, it proved to be quite complicated. I recently came ...
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Linear regressions with similar coefficients

If one has multiple similar dependent variables for which one wants to fit linear regressions y1 = c11*x1 + c10 + e1 y2 = c21*x2 + c20 + e2 y3 = c31*x3 + c30 + e3 ...
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Meta-analysis for case-control studies, confounding factors

Is there a way to adjust the pooled summary effect size (odds ratio) for confounding factors while performing a meta-analysis in R studio? I am performing a meta-analysis and I don't want to pool ...
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34 views

Pool redundancy analysis results from multiple imputations of missing data

I have a dataset that includes missing values, and I would like to carry out redundancy analysis using multiple imputation to fill in the missing values. So far, I have successfully created multiple ...
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1answer
71 views

What is the risk of not pooling data

Neglecting sample size, is there something that I can miss if I choose to model separately each of the levels of my categorical variable? To be more specific, I want to predict a binary outcome $Y$ ...
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123 views

Max-Pooling: Use Valid or Same Padding?

So Same padding allow you to design deeper networks, since there is a slower reduction in volume size. Also it improves the performance a lot of the times since it keeps more information than when ...
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Pooling descriptive statistics of categorical variables after multiple imputation

I am doing multiple imputation using the MICE package on R. My dataset consists of both categorical and continuous variables. After doing say 20 imputations, how should I go about pooling together the ...
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158 views

Paired vs. Pooled Inference… When is it okay to pair samples?

I understand that paired tests are usually done on sampling distributions that have some sort of linkage. But is there a definitive way to differentiate when to use a paired t test vs. pooled? The ...
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Can I pool these groups?

So I am not completely sure whether I can pool my groups or not to compare them, or if it would be better to compare them pair-wise. The purpose of this comparison is to test the efficacy of my stress ...
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How can random forest variable importance of a pooled sample be greater than variable importance of individual samples?

Here's what I have: a data set with 30 different questions measuring customer experience (on a scale from 1-10), and a question measuring "Overall Customer Satisfaction" (Q1). The data set is ...
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Comparing cage average values… weighted, pooled, nested?

I want to compare food consumption between three treatment groups. Each treatment group had 20 individuals, however, due to logistical constraints they were group housed in cages with 2-3 individuals ...
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100 views

Getting pooled F-values and p-values for multiply imputed data in SPSS?

When working with a dataset created via multiple imputation, SPSS pools some values but not others. For example, in multiple regression, I can get coefficients, t-tests for the coefficients, t-values ...
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How should we recalibrate weighting of the pooled dataset?

I have results from 2 surveys at the same year, The sampling method used in these surveys are different and I have sampling weights calculated (with respect to the population) in each study. The ...
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1answer
506 views

Pooled Covariance Matrix with very different amount of samples per class

I have a dataset with 10 classes, and want to estimate the covariance. It turns out that due to numerical stabilitiy, it is much better to use a pooled covariance matrix. Suppose I have $N$ samples ...
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152 views

CNN: correct way of reducing dimensionality of last feature maps

I want to reduce the features of the last convolutional layer of my CNN before connecting it to a dense layer to minimize the risk of overfitting. Lets say the feature maps of the last layer have the ...
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126 views

With lme4, is it possible to weight group-level random effects by similarity?

I'm creating a model with two group-level random effects: district (factor) and age (factor) and a response, ...
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Understanding the relationship between multiple variables

Having troubles interpreting the results of my pool() function I know what everything means except for the estimate, d and riv columns: ...
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141 views

3 Level Hierarchical Models in STATA; Null model fails to converge

3 Level Hierarchical Models in STATA; Null model failed to converge About the Dataset I am working with DHS (Demographic and Health Survey Data) data. DHS uses a two-stage cluster sampling process. ...
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Standardisation (normalising) for feature scaling in non-logged data for within transformation model

I wonder if someone could provide an insight for my case. I am interested in normalising my data to obtain unitless state that will allow me to use them in a quadratic model (not translog). Based on ...
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51 views

Weighting and Clustering in Pooled Data Analysis

I am working with DHS (Demographic and Health Survey) data. I have pooled data from about 25 countries taking 2 most recent waves from each country. My dependent variable is neghaz (negative of height ...
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109 views

Proof that the pooled sample variance is biased when paired comparison is not used when it should be

Given the model for what is meant to be a paired comparison design: $y_{ij} = \mu_i + \beta_j + \epsilon_{ij}$ $i = 1,2; j= 1, 2, ..., 10$ Eg. An experiment comparing the different in mean hardness ...
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19 views

What is the degree of freedom of a t-statistic when computed by using multiple samples of the two types of experiments?

Let's say I have samples 1, 2, 3, and 4. Out of these, 1 and ...
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116 views

How to calculate pooled deviance explained from gam model fitted with multiple imputation data set?

I fitted gam model using mgcv package with multiple imputation data set. I need to calculate the combined overall deviance explained. Is the approach used in combining r-square from multiple ...
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102 views

R Panel Data: Difference between Pooling OLS and Fixed Effect with only “individual” effect

I just estimated my paneldata with Pooled OLS or with the Fixed Effect approach. When using FE with the effect="individual" I get a higher adjusted R^2 than using FE with effect="twoways". So I would ...
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716 views

Is there an R function that performs LASSO regression on multiple imputed datasets and pools results together?

I have a dataset with 283 observation of 60 variables. My outcome variable is dichotomous (Diagnosis) and can be either of two diseases. I am comparing two types of diseases that often show much ...
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1k views

1D CNN for time series regression without pooling layers?

I am working on a prognostics task, where I predict the Remaining Useful Life of some equipment (i.e.: time steps remaining until failure). In order to do that, I use multivariate time series sensor ...
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100 views

Difference between pooled variance equations

I'm currently doing A-level Further Maths A2. I've seen two different equations to calculate the estimate of pooled variance. I do not know when to use which and what makes each significantly ...
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76 views

Simple mean or weighted mean of Fisher z-transformed correlation coefficients

I need to perform the average of a set of correlation coefficients $\rho_i$ with $i=1,\ldots,m$. I follow the standard prescription: apply the Fisher z-transformation to my $\rho_i$ ($z_i$ are the z-...
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49 views

Pooling estimates and variances with zero counts

I have a dataset with 10 different sampling groups. The sampling is done in order to maximize the ability to find events. The sample looks a little like: ...
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21 views

bias estimating the proportion in pooled population

Assuming we want to estimate the proportion of success and there are two stages. We will move to stage 2 only when the number of success is greater than equal to a threshold (say 5) in stage 1. And we ...
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524 views

What are the advantages of a random effects model versus a pooled OLS regression with cluster–robust standard errors?

Both models allow for explanatory variables that are time-invariant. I had thought that the advantage of a random effects model might be related to the fact that random effects models mitigate ...
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55 views

what is the standard error for hypothesis testing of two proportions using a z-test?

Let's say we are evaluating two algorithms. Algorithm 1 gets p1 = 80% conversion Algorithm 2 gets p2 = 85% conversion The two sample sizes are ...
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152 views

Pooling homogenous studies vs. using meta-analysis/bayesian

I am working with a student who has collected about 300 participants for his thesis. After collecting 100 participants, he analyzed the data. I had just recently read of a "mini-meta-analysis" ...
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33 views

Pooling Results from Bootstrapped Samples (Adjusted R-square and variable significance)

My manager is interested in using Adjusted r-squared to evaluate models and want to know how much does each predictor contribute to the adjusted r-squared to the final model. However, due to an ...
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How to combine observational studies

I am trying to show the releationship between a drug and an outcome in a particular setting. Using a systematic review, I have found 18 studies addressing this topic. Among those, the highest quality ...
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1answer
514 views

Connection between time dummies and time fixed effects

If i use time dummies in a OLS pooled regression, does it imply time fixed effects? Maybe to clear things up: 1)There is a pooled time -series-cross-section regression, the equation uses time ...
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1answer
1k views

Proof to obtain pooled variance equation [closed]

I was checking the definition of pooled variance, and although I think it makes sense intuitively, I was wondering how can one obtain that estimator. For the case of only one group, I understand the ...
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55 views

Short Sentence Generation using CNNs

I am investigating whether building a classifier for sentence classification using CNN can be used for sentence generation. Say, we are classifying news articles' titles (classes such as sports, ...
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126 views

Asymptotic Variance for Pooled OLS

I am trying to prove, under the assumption $E[u_t^2x_t^Tx_t]=\underbrace{E[u_t^2]}_{\sigma^2}E[x_t^Tx_t]$, that the $$AVar[\beta_{POLS}]=\sigma^2 E[x_t^Tx_t]^{-1}$$ My result: $$\begin{eqnarray}AVar[...
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Pooled variance for post hoc tests for contingency table $\chi^{2}$ tests

The 2-by-2 contingency table test provides an alternate hypothesis testing approach to the $z$ test for proportion difference. Conveniently enough, a 2-by-k contingency table test provides an omnibus ...