Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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Use auxiliary range information to improve the accuracy of regression

I have built a model using GLS with reasonable success. The model has the form $E[Y]=g^{-1}(X\beta)$. However, I recently obtained some new data $Z$. For each observation $y_i$, there might be 0 or ...
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31 views

Regression - What to do with insignificant variables?

Please pardon me if you find this question very silly but this doubt has been troubling me for some time now whenever I want to run a regression. I am working on SAS. I have a dataset which has ...
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32 views

What are the key steps in solving Machine Learning Problem

I am trying to make a summary to myself, what are the key steps for solving a Machine Learning problem. I tried to read good books, talked with peer, discussed many issues here, checked many web based ...
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12 views

fixed vs random regression in panel data

Anyone could explain me the differnce between fixed and random effects concerning panel data regressions? With examples? I have actually used panel data regressions for some of my predictive models ...
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12 views

What mean coefficients in autoregressive model and how calculate them?

What mean coefficients in autoregressive model and how calculate them ? yt=c+ϕ1yt−1+ϕ2yt−2+⋯+ϕpyt−p+et, ϕ1, ϕ2 ... This coefficients are "fourier transform"? Can ...
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32 views

What explains the correlation between the slope and intercept?

If $R^2$ explains the variation explained by a model, what explains the correlation between the coefficients given for a slope parameter and an intercept? I have been thinking of it in two ways: If ...
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11 views

k-fold cross validation for LASSO regression model

Assume we have a simple linear regression model expressed as $Y= X \beta + e$. We know that finding the regression coefficients $\beta$ using the LASSO method is performed by penalizing the Least ...
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18 views

Role of Distribution , likelihood function, and MLE in regression ?

I'm currently a beginner in learning statistics. In regression part, we started to learn (software) using MLE method for estimating parameters in the models. In order to calculate MLE, likelihood ...
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9 views

Different kinds of minimax convergence rates

Stone (1980) provides a minimax rate of convergence $a_n$ for pointwise estimation of a regression function, defining it as $\lim \inf_n \sup_{\theta \in \Theta} P_\theta( \hat{T}_n - T(\theta) > ...
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33 views

Logistic regressions questions about line fitting vs. probabilistic interperetation

Suppose I have data points $(x_1^1, x_2^1), (x_1^2, x_2^2), (x_1^3, x_2^3), \ldots$ in $\mathbf{R}^2$ that fall in one of two classes, $y^i=0$ or $y^i=1$. I can find a linear separator for these ...
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18 views

Correct interpretation of linear coeffs for 1 interaction, 1 numeric, 1 categorical

Good day, XValidators. This is my 1st question in the community. I'm at my wit's end here. Nowhere in the interwebz nor in youtoubeland can I find an answer to the following: Assume you have this ...
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21 views

Regression on Inferred Variables

Given a set of labels $y$ and design matrix $X$ we often compute a linear regression to find a set of parameters $\hat{\beta}$ such that $E[y|X] = X\hat{\beta}$. However, how does one perform ...
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14 views

How SAS handles missing values while fitting linear regression model

While fitting a linear regression model in SAS, if the dataset has missing values (either missing y, or missing x or both), will SAS just ignore the records that have at least one missing value(y,x)? ...
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1answer
10 views

Gradient Scores from Binary Logistic Regression

My research concerns the language of Alzheimer's patients. As the disease progresses, their language becomes more concrete and less abstract - they seem to 'lose' their abstract vocabulary more ...
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16 views

Applying parametric tests on non-parametric data

I'm doing a research and I have some concerns, and I'd appreciate your kind assistance on them. Basically, I'm designing an instrument to measure something (a single dependent variable), and I'm ...
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1answer
18 views

Merging observations in Gaussian Process

I am using Gaussian process (GP) for regression. In my problem it is quite common for two or more data points $\vec{x}^{(1)},\vec{x}^{(2)},\ldots$ to be close to each other, relatively to the length ...
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1answer
29 views

how should I do regression analysis where response is number in each category

I try to find genes that related to output which is numbers in three category. The simplified analogy is: first we take an zygote and measure the expression of a gene, and clone this zygote to many ...
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13 views

R survreg returns reciprocal of incidence rate ratios?

I'm working through some poisson regression for survival data using R. As I understand it, the exponentiated output from survreg with dist = "exponential" should give the incident rate ratios. I ...
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1answer
39 views

Interpretation of linear regression where the outcome can only possibly cause the value of predictors and not viceversa

We want the verify the association between artificial pregnancy (artificial insemination) versus natural pregnancy and a series of pregnancy conditions (hypertensions, diabetes, etc). We first ...
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12 views

Interpreting interaction term via margins command? [on hold]

I am using Stata. I regressed test score on a wealth dummy (high/low) and a maternal education dummy (high/low) and some control variables, among them age (3,4,5 and 6 years), in a linear regression. ...
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1answer
17 views

Advice on a model or approach to layered dataset

I am attempting to develop a model to estimate the number of people in a space based on the Wi-Fi Traffic. At present, I have a dataset (in xml) which is structured like the following: ...
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7 views

How to use co linear variables in developing a model

I am trying to develop a model to predict a price which depends on market indexes, Market indexes are correlated (they rise and fall together). Price also changes in same direction with indexes. I ...
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8 views

large difference between pearson and deviance residuals

pearson deviance 7.46917 2.8423 6.85298 2.78224 I am fitting logistic regression model in SAS. What should be reason of large difference between pearson and deviance residual as mentioned above ?
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30 views

Can I use Cox Regression here?

I have a data-set where I want to do a regression of survival probability given amount of drug injected into a subject. The more drug injected, the less likely the subject will survive after say, 3 ...
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2answers
39 views

How should I check the assumption of linearity to the logit for the continuous independent variables in logistic regression analysis?

I am confused with the assumption of linearity to the logit for continuous predictor variables in logistic regression analysis. Do we need to check for the linear relationship while screening for ...
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34 views

Why would I need both a validation set & a test set if I'm not selecting a model?

I have a dataset with two features and one outcome. I was asked to separate the data into three parts such that 70% of the data is a training set, 20% is for validation and 10% for testing. The model ...
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24 views

Interpreting circular-linear regression coefficient

I'm trying to use the circular package in R to perform regression of a circular response variable and linear predictor, and I do not understand the coefficient ...
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1answer
87 views

Model selection, issues of judgement

I have a general question on model selection strategies in regression models. In my research, the main goal is rarely prediction but almost always estimation of effects of certain variables. I have ...
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1answer
29 views

Difference between modelling and testing association

I have data set with binary outcome, with 5 continuous covariates and 4 discrete covariates. I am little confused as to how I test for association, for the discrete covariates, I used a chi sq test, ...
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17 views

Segmented Regression With Control Group Implementation and Interpretation

I have been reading the following paper on segmented regression for interrupted time series - Wagner 2002 and wanted to learn a proper analysis of such data where there is a control group. The paper ...
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20 views

Constraining coefficients in linear regression

I am trying to estimate a model of how rail freight shipping rates are effected by a number of different variables, including the price of fuel. There is such little variation in the price data that ...
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1answer
36 views

Forecasting - Population Death Rates

Wondering if you can help me out with this problem: I have 2 closed populations of products (call it Product X, and Product Y). Population Size of each product 10 million each (Product X = 10 ...
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21 views

Partial Least Squares regression

Assume we have a simple linear regression model expressed as $Y= X \beta + e$, where $Y$ is a vector of size $n \times 1$, $X$ is a matrix of size $ n \times p$, $\beta$ is the regression coefficients ...
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1answer
26 views

Three Different Regression Results… Why is one so weak compared to the other two?

I have a data set I'm working with, it's roughly 450K rows of data. I'm breaking the data out from a certain column, and that column has three results. After that, I ran a regression analysis for each ...
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1answer
16 views

Testing a single time-series for changing variance structure (Heteroscedasticity and Volatility Clustering)

I would like to assess a single time-series for a changing variance structure that might be leading to spurious variance estimates when that time-series is used in regression. In my head two terms ...
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Changing polynomial degrees leads to different coefficients in Fuzzy RDD

I am running a Fuzzy RDD and I am getting some unusual results, the coefficient of interest changes sign and significance with different polynomial specifications. When using a linear polynomial ...
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14 views

Interpretation of odds ratio in logistic regression

In the study of birth weight (low or normal) of a child, the "birth term" of the child has been considered as a risk factor. The birth term has two categories: premature and full-mature.The following ...
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association between discrete variables and continuous variable

I am having little difficulty with understanding the difference between, testing association between two variables and modelling them. Say I have binary outcome x(sold, not sold), and i have all ...
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19 views

Could Use Assistance On A Work Project [on hold]

This might be a little unorthodox, but I could use some assistance on a work project. I work for a small company. We don't have any formal data sciences or analytics department. I was tasked with a ...
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14 views

Improving estimates of linear system regression when parameters are unevenly weighted

I have a system with a linear model $ax + by = c$. I can adjust $a,b$, measure $c$ (with some error in the measurement) and then use linear regression to estimate $x,y$. The problem I'm running into ...
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20 views

Regression analysis of a correlation coefficient

I have a time series of the 250 day historical correlation and I need to determine what causes this correlation to change as different explanatory variables change. Is there a way that I can regress ...
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13 views

Cross country OLS regression

Need help as this is my very first experience with panel data.I am studying impact of stock market on economic growth(GDP per capita). for that, panel data consisting of 60 countries from 2001-2011 ...
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1answer
27 views

Comparing Height of Web Page against Scroll %

I have a collection of 108 data points in the following format: page height | % of users who scrolled upto 25% of page | 50% | 75% | 100% (full page) I'm trying ...
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3answers
215 views

How do you call multiple linear regression when it has an interaction term?

I'm writing a report and need to be precise but concise in the abstract. Currently I called it 'multiplicative multiple linear regression'. But when I Googled it, not much came up. In the same vein, I ...
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6 views

Problems facing in fitting ordinal regression model on life satisfaction data

While running an ordinal regression analysis of life satisfaction data SPSS, I got the following warning: There are 148 (65.8%) cells (i.e., dependent variable levels by combinations of predictor ...
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6 views

Moderation Analysis: Correlation Coefficient or Fisher's r to z

I was wondering if anyone knows whether correlation coefficients or using the fisher's r to z transform may be more appropriate to enter as a predictor in a moderation analysis? Thank you for the ...
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1answer
29 views

Gaussian processes ordinal regression in R [closed]

Is there any ordinal regression using gaussian processes implemented in R? I made a research in the Internet, but I didn't find anything.
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Allocation of design points in an experiment

I would like some hints with the following problem. Thanks for any help in advance. An experimenter wants to design an experiment for estimating the rate of change in a dependent variable Y as an ...
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Compare two simulations results of similar systems

I am simulating transcription regulation (a biological process) by four different mechanism using Ordinary Differential Equations. I am not sure about how to compare two different simulations (the ...
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31 views

Linear regression interpretation

Lets say I run a port. There's this ship coming with watermelons and melons. They have multiple containers, which I cannot open, with mixed watermelons and melons. From the source port, the ...