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

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Fixed / Random Effects Model

I have the following kind of panel data set, without a time variable. 20 countries are the panel variable and provide data on 48 other countries. The independent variables are 6 (intercorrelated) ...
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clustering of singular values

let us consider following graph of singular values i want to make some kind of clustering of these data,namely to seperate main components from non main components,let say signal components ...
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1answer
123 views

What is the difference between multiple regression & mutivariate regression?

I have data on GDP growth as a dependent variable and growth in main production sectors of Pakistan such as mining, electricity, communication, manufacturing and electricity. I am supposed to run a ...
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1answer
6 views

Difference between ep-SVR and nu-SVR (and least squares SVR)

I am trying to find out which SVR is suited for what kind of data. I found out 4 types of SVRs: epsilon, nu, least squares and linear. I understand linear SVR is more or less like lasso with L1 Reg. ...
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Offset variable in Poisson regression makes model worse

I'm using a Poisson regression to model count data (number of orders). My observation lengths are different, so I tried to include an offset variable in the model. The problem is that when I estimate ...
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16 views

How to interpret Weka logistic regression output for a nominal attribute and its coefficients? [on hold]

Kindly help me interpreting the output of logistic regression in Weka. I have a data set. Below is the arff file. There is one numeric attribute and 3 nominal ...
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How do you interpret Ordinal Logistic Regression output without an adjusted R-squared Equivalent (and additional clarifying questions)?

I've gotten fairly good at multiple linear regression recently, and I'm now trying my hand in ordered logistic regression -- but I'm having trouble analyzing some of the results. Anybody who could ...
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1answer
81 views

Do Beta weights from regression have error terms?

I am looking at standardized regression weights (i.e., Beta weights). I was thinking of reporting the errors next to the weights in a figure, but upon some thought I was debating whether such errors ...
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54 views

How to compare whether the coefficients of two independent variables statistically different from each other?

If I have two independent variables and they are dummy variable along with other independent variables and I run a linear probability model, I want to compare whether the coefficients of two dummy ...
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Construct matrix of stacked variables in VAR regression

I am trying to NOT use packages for the estimation of models in order to have a deeper understanding of how things work. Currently, I am trying to estimate a VAR(1) (vector autoregression of first ...
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22 views

Help interpreting R linear model fit [duplicate]

I have observed variables power$values. I am trying to model this process using a second set of observations, such that $P = M\cdot X + B$. $P$ is the function ...
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1answer
24 views

What preponderance of a single outcome renders binary logistic regression ineffective?

This question was motivated, but is separate from, the question I posted here: How can I improve the predictive power of this logistic regression model?. In that case the 'cancer' outcome was ...
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3answers
210 views

How can I improve the predictive power of this logistic regression model?

I am using SPSS to analyze a data set which aims to predict whether individuals have cancer based on five symptoms (a, b, c, d, e). In this data set most individuals have cancer. I ran a Binary ...
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2answers
27 views

what does the correlation of Random forest regression tool in R represent

I've built a random forest model (regression model) using randomForest package in R, and I calculate the correlation between the predicted values and the actual ones in order to know how the trained ...
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1answer
21 views

Is it ok to spit non-normal variables in tertiles and put them into multivariate regression models?

I am now reviewing a paper in which the authors decided to predict a DV through linear regression using, beyond other variables, dummy variables obtained from a tertile split of continuous variables, ...
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1answer
31 views

SPSS linear regression - variables that are percentages

I have some data about music styles played at festivals. It looks like this: Based on this (and other) data, I'd like to make a model to explain the price of a ticket for each festival. However I'm ...
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29 views

How to do Regression Discontinuity Design in R [on hold]

I am having trouble with doing regression discontinuity design in R. Could anyone show me a syntax for R to do RDD? The exercise I have is y= wealth x=winning margin covarites= education, past ...
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1answer
27 views

Cardinal data as dependent variables

I wanted to find out if there are any implications to using OLS when i have cardinal data as dependent variables. So my dependent variables are counts of a certain outcome and they exist as natural ...
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35 views

How to make stochastic gradient descent algorithm converge to the optimum?

(Background info taken from my blog) In logistic regression, the hypothesis function, which models the relationshiop between the dependent variable $P(y = 1)$ and the independent variable $X$, is : ...
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29 views

Explanatory power of variables in multiple regression

Suppose that I have a regression model with two explanatory variables: $Y = b_0 + b_1X_1 + b_2X_2 + \epsilon$ The determination coefficient $R^2$ measures the amount of variability in the response ...
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Feature scaling for classification and regression

Is it true that one should generally scale each of the features before feeding them into common classification models such as Support Vector Machine, Logistic Regression, etc? What about for ...
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Problem with year as a factor GLMM

So I need to do a GLMM, I do it this way, with package lme4 glmer(y~x1+x2+x3+year+(1|x4),family=binomial In my data, year is a factor (4 levels). So when I run my glmer, I have my result like this x1 ...
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Are these descriptions of batch gradient descent algorithm conflicting each other?

The first one is from Andrew Ng The second one is from Francis Bach I might be a little confused, but why is there a summation of partial derivatives in the second description and none in the ...
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Standardizing count variables in panel data with overdispersion - R or Stata

I'm running a regression where the dependent (response) variable is a highly dispersed (slightly zero-inflated) count and the explanatory (independent or predictor) variables are continuous, counts as ...
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What is multi run lasso regression?

I have problem in understanding of multi-run lasso regression. Basically, I know what is lasso regression, but don't know what is multi-run lasso regression, which sometimes I see literatures. Does ...
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What is PRINCIPAL HESSAIN Direction Model, how and where can I use it?

I'm a M.Tech student going through my academic project-work, here I have asked to develop a optimal design and a best equation to fit the data for a Leaching, Solvent extraction and Electrowinning ...
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57 views

confidence intervals for values estimated from the nonlinear regression model

I have a question about nonlinear regression and confidence intervals for values estimated from the model. Here is my problem. I have sets of data where $X$ is the logarithm of the dose of a chemical ...
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Fit a GARCH (1,1) - model with covariates in R

I have some experiences with time series modelling, in the form of simple ARIMA models and so on. Now I have some data that exhibits volatility clustering, and I would like to try to start with ...
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Parameter tuning in lars (lasso) matlab

I am trying to use lars (matlab implementation:http://www.ece.ubc.ca/~xiaohuic/code/LARS/LARS.htm). I want to do a leave one out cross validation on my data using this code. I have the following ...
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37 views

Multiple linear regression through orthogonal matrices

An example of linear regression could look like: $min \sum_{i=0}^{m}||x_i A - y_i||_2^{2}$, where ${x_i, y_i} \in \mathbb{R}^n$ and $A \in \mathbb{R}^{n\times n}$. I am interested in knowing how do ...
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58 views

How to interpret a regression that includes GDP, GDP per capita, and population

While GDP per capita = GDP / population and are obviously related, these three measurements are not perfectly collinear and can be included in OLS just fine. ...
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1answer
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Goodness of fit of a SUR model

I know that McElroy R^2 is a measure of goodness of fit for Seemingly Unrelated Regressions (SUR models), but how can one judge that the estimated equations are well fit by using the McElroy R^2?
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How to fit a model for a censored binary outcomes?

Suppose I have a data frame such that: ...
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Difference-in-difference more than two periods [on hold]

I try to use a difference-in-difference design in my study. But I have three periods. So I would like to know how I could run my difference-in-difference analysis on Stata with more than two periods.
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What does it mean to “fit a regression function” and then use it to update other functions?

Referring to the algorithm on page 11 in this paper on boosting algorithms, I really don't understand step 2, (ii) and (iii). What does this mean: (ii) Fit the regression function $g_j^h (x)$ by ...
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2answers
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Why do both the VIF and tolerance statistics exist, when the latter is just the reciprocal of the former?

Is taking the reciprocal helpful in some way, or is it just a matter of historical accident that there came to be two terms to describe the same thing? (From the Wikipedia page.)
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Treating ordinal variables as continuous for regression problems

In the social sciences I have encountered that it is common to treat ordinal variables as continuous, for example variables originating from rating or Likert scales (strongly disagree, disagree, ...
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49 views

Combining summary statistics

Currently I add Var1+Var2=VarSUM12 and then perform a linear regression on VarSUM12~x to obtain test statistics for x and get insight into weak associations that are present across Var1 and Var2 with ...
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Analyzing relationship between two Likert-items (is it possible?)

I am a student and am new to statistical market research. Is it possible to analyze the dependence of answers to one Likert-type item on answers to another Likert item (predictor)? If so, what test ...
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Why would I want to use my data this way, and what am I supposed to do with this regression?

I'm writing an essay on the effects of M&A announcements on stock prices. I understand most of the requirements perfectly fine, but I'm stumped on one particular part of the essay. I have for ...
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1answer
42 views

How should you fit ANOVA and linear regression models, if the equal variance assumption is violated?

This is my topic for the paper I'm working on for an undergrad stats class. It's supposed to be 20 pages... and I'll be honest, I understand very little beyond the basics and am over my head. From ...
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61 views

Piecewise regression

I have a time series where I want to fit a piecewise regression equation. Now the problem occurs when I try to fit equations of different degree in different segments of the series. Please provide me ...
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69 views

How to get the regression from a plot?

I have a dependent variable C and an independent variable VPT. VPT is the average volume per ...
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28 views

Considering correlation of independent variables in regression model

I have one dependent variable C and four independent variables: S SD ...
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39 views

Can a Linear-Log model be used instead of Robust Standard Errors?

If your regression model has heteroskedastic residuals, one should calculate White Standard Errors that correct for the mentioned heteroskedasticity. If the residuals are also autocorrelated one ...
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53 views

Interpretation of Maximum likelihood estimation

I have some problem to interpret the result of MLE estimation : Is it possible to get some advise about how to interpret it? the log likelihood function : $\sum^{n}_{i=1}\log\left( \phi\left( ...
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1answer
21 views

Dummies instead of the Chow test

I have found somewhere a mention to the possibility of using dummies variables instead of the Chow test to test whether the coefficients in two linear regressions on different data sets are equal. ...
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149 views

Testing whether two regression coefficients are significantly different (in R ideally)

If this is a duplicate question, please point to the right way, but the similar questions I've found here haven't been sufficiently similar. Suppose I estimate the model $$Y=\alpha + \beta X + u$$ ...
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What statistical tests for headache journal?

I track my pain levels in an online spreadsheet along with daily habits and trigger events. I want to test whether changes in my pain over time follow a trend (not concerned whether it is linear or ...