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Can I summarize different forms of intraclass correlation coefficients (ICCs) descriptively?

There are various forms of intraclass correlation coefficients (ICCs) that differ in terms of their "model," "type," and "definition" (Koo & Li, 2016). So my question ...
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Understanding rare definition of the likelihood function and corresponding posterior from google research paper

Reading the paper https://storage.googleapis.com/pub-tools-public-publication-data/pdf/b20467a5c27b86c08cceed56fc72ceadb875184a.pdf i came across a rare definition of the likelihood function that in ...
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How to combine Cause Specific Hazard model

Lets say I need to model the survival probability for death from heart disease (noted $H$). There is a competing risk in the study which is non-heart disease (noted $NH$). $H$ and $NH$ are competing ...
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How to evaluate likert items with quantiative (numerical) data

While testing some software I had users fill up a survey which asks questions in Likert scale (1-5) about the 3 different states of the software. These states were: one without aid, one with aid in a ...
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Why is simr constantly giving me erroneous power results in R?

No matter what model I fit in lmer, it seems like simr never gives an accurate read of what the data is doing. For example, the ...
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Finding the most representatives of each cluster

I'm using CLARAN algorithm to cluster big spatial dataset using R studio. My dataset was clustered to three groups. What I need is to sample the 100 observations the most representatives of each ...
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1 answer
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Estimation vs Prediction Vs Forecast

I already read the q/a's from here and here. These answers are quite a bit complicated for me. I need something easy to understand and explain to any interviewer. I read lots of articles like; What is ...
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  • 625
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1 answer
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Are T-tests good choices here?

I would like to test if two groups of participants (dark-eyed and light-eyed individuals) respond to a drug differently over time. The hypothesis is that the drug reaches its peak effects sooner but ...
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95% Confidence Interval should mean 95% probability that the interval contains the true parameter

What the image below represents is true. Black intervals belong to samples which properties allow produce CI that contain the true parameter, and purple intervals belong to samples which properties ...
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R language (kumaraswamy generalized pareto distribution) [closed]

What is the R programming code for kumaraswamy generalized Pareto distribution.
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When forecasting by Moving Average Process, how is the error term ε calculated from data?

For simplicity, parameters have been trained. In the case of the AR process, it is able to forecast using observed data. However, the ε used for the MA process is not present in the data. I would like ...
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Unbiasing estimator of $\|\Sigma\|_F^2$

I have access to samples of some distribution with second-moment matrix $\Sigma=E[xx^T]$ and need an estimate of $\|\Sigma\|_F^2$ (which can be used to set optimal size for LMS) My space has millions ...
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Errors-in-variables random effects meta-regression

I would like to perform an error-in-variables random effects (DerSimonian and Laird method) meta-regression, but I do not know how one goes about doing this. Does anyone have any advice on if this is ...
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  • 21
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Comparing GAM models with/without fixed effect interactions using REML versus ML

I have several GAM models fit with package mgcv that share the same smooths and random effects groups. I would like to compare support for whether interactions ...
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  • 67
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0 answers
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How to show linear combination of independent, but non-identically distributed Bernoulli's is asymptotically normal?

Summary I am curious about whether there exists theoretical justification to say a linear combination of a sufficiently large number of independent (but not identically distributed) Bernoulli random ...
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5 votes
2 answers
17 views

Does introduction of new variable always increase the p-val of existing ones?

I am doing some work that requires some estimates of gasoline oil demand elasticity on certain countries. After doing various econometric measures such as instrumental variable, I was able to get ...
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  • 213
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0 answers
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How to interpret Model Likelihood Ratio Test for ordinal logistic regression model in R?

I would like to evaluate the ordinal logistic regression model using function orm() in r. How can I interpret the output of Model Likelihood Ratio Test here? Does it mean that the larger LR Chi2 value ...
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ROC curve not forming the usual shape

I have a situation where I have 4 histograms on the same plot - let's say for example these are the weights of 4 different animals: lions, tigers, wolves and deer. I am trying to classify new data by ...
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14 views

How to plot interaction term in logistic regression in R

I'm working on the logistic regression with interaction term between gender and education years as below. gender is a factor varibale with two value and eduyears2 is a numeric variable. and the ...
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1 vote
0 answers
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Hazard ratio from Royston-Parmar model (flexsurv::flexsurvspline)

I have a time dependent covariate with two categories (lets call it T), which I have modeled using the Royston-Parmar model from flexsurv package as following. ...
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  • 365
2 votes
1 answer
16 views

Is it okay to leave a treatment group out of an analysis?

I am currently analyzing data from an RCT. The primary findings from the RCT have been published and we are now examining the data further. In brief, the RCT examined the effectiveness of a new ...
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1 vote
0 answers
17 views

Hacked OLS Regression vs True Beta Regression?

I have a regression problem where I have known probability-like values (and some correlated features) that I need to model for future applications. My understanding is that a beta regression might be ...
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  • 226
1 vote
0 answers
4 views

Average Sample Size For Curtailed Double Sampling Plan

I am currently implementing double sampling. The goal is to accept or reject a lot by only sampling a few instances from it. In a two-stage testing procedure (double sampling) one first draws a ...
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  • 91
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Questions about the exact covariance - matrix and Adjusted Total Variance

Good evening everyone. Regarding the topic related to Sparse PCA. For example, in "Sparse Principal Component Analysis Hui ZOU, Trevor HASTIE, and Robert TIBSHIRANI" the authors mention the ...
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13 views

Binary Classification using Machine Learning Models for longitudinal data in R

So I have longitudinal data with a binary target variable, and I'd like to perform binary classification using a random forest, xgboost, and glmnet (ridge/lasso/elastic net) model. Is this possible to ...
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1 vote
0 answers
9 views

dealing with zero inflation in the regression model

I have a longitudinal data, with different follow-up number for individuals. I have considered measurements for each individual as a curve which I already smoothed them, then calculated the area under ...
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Reasoning about regression models with control variables and timevariant/invariant coefficients

I am trying to grasp how different regression models with and without control variables can be interpreteted. My aim is to capture how certain parameters in my model changes w.r.t time whilst ...
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0 answers
12 views

Insignificant results when adding interaction terms in path analysis (R)

I am using lavaan package in R for performing path analysis. I do have a significant chi-square p value and other index (CFI, RMSEA, etc) in my original path ...
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  • 23
2 votes
2 answers
34 views

Statistical Signifance Test for discrete data

I'm fairly new to statistics and want to perform a statistical analysis (calculation of p value) for data I collected, but I'm unsure if I'm doing it correctly and would like some feedback/help. I ...
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  • 23
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0 answers
17 views

Scikit-learn QuantileRegressor memory allocation error. No issue with statsmodel QuantReg with the same data

I'm trying to fit a quantile regression model to my input data. I would like to use sklearn, but I am getting a memory allocation error when I try to fit the model. The same data with the statsmodels ...
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  • 1
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0 answers
4 views

How to map states between two different Hidden Markov Models (HMM) for a classification problem?

I am currently working on a classification problem for timeseries analysis which uses two different Hidden Markov Models. I fit a model to the sample of subjects belonging to class A, model A, and ...
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1 vote
0 answers
8 views

Why two dimensions MCA that may represent 40% of variance is enough to constructing socioeconomic scores?

The research paper I am putting the link to and many others when using MCA to formulate socioeconomic scores, they tend to use only two dimensions eventhough most of the variance is not represented by ...
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Is it possible to define the wavelet phase difference for only one signal?

The wavelet phase difference between two signals $x(t)$ and $y(t)$ is derived using the real and the imaginary part of cross wavelet transform $W_{x,y}$. (Let us consider e.g. the Morlet wavelet as ...
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  • 197
4 votes
2 answers
28 views

Deal with categorical variables in regression with overlapping classes

I want to perform a OLS regression analysis on some venue hire data (to get cost of venue hire). I have many categorical variables and some of them have correlated / duplicated information e.g. An ...
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0 answers
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post-hoc multiple hypothesis testing for Kolgomorov-Smirnov comparisons. Is it really necessary?

I have to compute the empirical Cumulative Distribution Function (eCDF) for a set of spectra to compare a query spectra (QS) to this reference set. So, the eCDF of one spectrum will be compared to ...
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1 vote
0 answers
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How to interpret LME Estimates for an interaction effect that contains two continuous variables [duplicate]

I am somewhat confused about how best to interpret the results of my logistic mixed effects model. I have two variables, confidence (continuous, 0-100) and meta-d', which can range from -0.5-2. From ...
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30 views

Combining standard errors of two separate variables

I have a dependent variable associated with a SE and an independent variable associated with a SE. I would like to weight my regression such that both of these SEs are taken into account. What is the ...
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1 vote
0 answers
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The implications of using MCMC normalization algorithm output as input in a separate normal linear model (and similar combined approaches in general)

Background I am a statistics intern (not assigned a supervisor yet) in a medical research institute. I’m exploring methods for network analysis in the context of multi-omics data, focused on microbial ...
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3 votes
1 answer
31 views

Finding standard devition of unknown but non-normal distribution

I have a sample of ~3,000 star systems, and I've found the distribution of a particular parameter. I'd like to find the standard deviation of this distribution, and so I've used the standard ...
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  • 41
0 votes
1 answer
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How to properly impute values on the test set using imputer (missForest)

I'm trying to impute some missing values on my dataset $X$. So first I shuffle and split data to obatin the train set X_train and the test set ...
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  • 269
0 votes
0 answers
18 views

How do I interpret changing signifiance depending on fixed effects used?

I am currently running an analysis with a fixed effects regression on whether name similarities between mutual fund investors and leadership of invested company has an impact on the weight that ...
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0 votes
0 answers
8 views

Comparing the rank sums of two different ordinal variables with different points (Likert scale) in two groups?

I have two different variables (both use Likert scales) in two groups. One variable has a four points scale and the other has five point scale. I assume that I can use the Mann–Whitney–Wilcoxon-test (...
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0 votes
0 answers
11 views

Comparing percentages when the group sum is not 100

Wondering if my method here for coding qualitative research data is valid. My raw data looks like this: Contains apples Contains bananas Contains pears Cart 1 x Cart 2 x Cart 3 x x Cart 4 x x ...
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0 votes
0 answers
10 views

(Self Learning) In K fold cross validation, how are initial lambdas chosen before hold out scores/MSE calculated?

I am learning about cross validation so I can use the glmnet package to perform LASSO. I can tell this is a rudimentary question, but I cannot find a resource that explicitly answers my question (or, ...
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1 vote
1 answer
42 views

What metric does the 95% confidence interval of a 2-sample t-test cover?

I'm trying to better understand what the 95% confidence interval is supposed to cover (in the context of a two-sample t-test). I had always been under the impression that the 95% confidence interval ...
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0 votes
0 answers
18 views

Assign points to their respective distributions with a one to one correspondance

I have to determine what are the likelyhoods of four points being associated with four different distributions. Knowing that they can only be part of one and only one distribution at the given time. I ...
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0 answers
5 views

Lipschitz constant for lasso-type problems

I've read in many papers about the Lipschitz constant, such as here on page 105/106, in that it can be used to determine the optimal step size in a proximal gradient algorithm. I have two questions: ...
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0 answers
7 views

Sum of dependent multivariate gaussians

Note: I have already seen this Wikipedia article, and similar questions on this website: 1. Given two dependent multivariate Gaussian random variables, is the sum also a multivariate Gaussian? $X \sim ...
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  • 1
0 votes
0 answers
4 views

BNLearn Bayesian Networks - how is the structure decided?

I'm currently playing around with BNLearn on Python, and creating BN's from Pandas datasets. I'm not really sure why/how the package decides on the structure of the BNs it creates; see for example ...
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0 votes
0 answers
12 views

Average marginal effects for censored regression (Tobit) in R

I would like to calculate average marginal effects for a Tobit regression in R. margEff.censReg can calculate marginal effects at the mean, but not average marginal ...
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