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

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Optimum value of minlev in function combine.levels

I have a dataset of 306967 rows and 23 columns, and I am building a regression model for predicting a factor based upon 6 other iid variables. Doing this I encountered an issue of large no of levels ...
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16 views

Interpreting coefficients of Regression Model (Mincer Model)

Hi all, I am an undergraduate student who is currently doing an assignment. I am now facing a few problems which are:- 1) Age is usually a positive return to wage, but in my regression output, ...
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1answer
16 views

Estimating finite sample bias for Instrumental Variables

Are there ways to estimate the finite sample bias with instrumental variables? I guess this would be conditional on assuming some structure to the problem and also would involve simulation, but, at ...
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3answers
44 views

When to divide data into training & test set in logistic regression?

I am using Logistic Regression in a low event rate situation. Overall universe: 46,000 Events: 420 Conventional logistic regression models divide the data into ...
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1answer
46 views

Why does non-normally distributed errors compromise the validity of our significance statements?

There is a normality assumption when it comes to consider OLS models and that is that the errors be normally distributed. I have been browsing through Cross Validated and it sounds like Y and X don't ...
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22 views

Interpreting regression coefficients of log(y+1) transformed responses

I have measurements $y_1$,...,$y_i$,...,$y_n$ taken from a set of replicates in a factorial designed experiment. In order to use a linear regression I define my response $z_i = log(y_i + 1)$. The ...
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1answer
14 views

Signs on logistic regression betas flip relative to observed - expected counts from chi-squared test

I conduct a chi-squared analysis on some bins and conclude that an association between the bins and an event exists. I then calculate logistic regression coefficients to validate my hypothesis. Also, ...
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9 views

Using non-stationary time series in basic regression models

I know that non-stationary time series data cannot be simply used in OLS regression. But if I take the first difference and the log of the variables, making them more stationary around zero, can I use ...
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42 views

Using non-stationary time series data in OLS regression

I am using 1983-2008 annual data to test if both gini coefficients and gross national saving in China and the US can affect the US current account balance. The data seem to be non-stationary, but I am ...
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22 views

Naming of dependent and independent variables in simple linear regression

I'm currently doing some self-study on Simple Linear Regression. I came across the terms "dependent variable" (eg. Sales volume) and "independent variable" (eg. Advertising budget). I am curious to ...
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8 views

What is the practical array implementation of a regression function on a multidimensional array and reusing it?

I'm going through an algorithm that does regression on some training data. My objective is to practically implement this algorithm. The training dataset $X$ consists of $n$ samples, where n = 10. Each ...
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Differences between groups using proportions

I am doing two analyses. First, I want to compare performance of two groups (p<.05), with the independent variable being proportional data (total number of categorical responses/total number of ...
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4answers
59 views

How to deal with curvature in residuals plot

I am trying to do a multiple linear regression in R but am having some problems. I have a set up where I am trying to develop a multiple linear regression model for one variable (y) using six other ...
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33 views

Power transformation using Box-Cox transformation

I have a dependent variable Cost and an independent variable VPT. I want to perform a power transformation on ...
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1answer
64 views

How to explain control variables and interaction effects

I'm a bit stuck on running a GLM between 3 continuous variables in R. I can't make them categorical as it removes the significance. I have two questions. I'm analysing data on eggs. I had read that ...
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11 views

Empty significance in SPSS linear regression

I got a weird result with linear regression: there are empty significances. I use 'Stepwise' method, so it should drop the inadequate variables. (Of course the "000" Betas are confusing too.) What ...
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1answer
25 views

Interpreting Labour Economics regression model

Instrumental variables (2SLS) regression Number of obs = 603 F( 5, 597) = 41.96 Prob > F = 0.0000 R-squared = 0.1386 Root MSE = .26523 ...
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6 views

Non-Normal residuals after Box-Cox

I applied Box-Cox on a regression model with heteroscedasticity. Although the transformed model looked better than the original, it still showed signs of heteroscedasticity. What else can I do after ...
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1answer
30 views

What exactly does the 'boxcox' function in R do?

I am familiar with the power transform family and I know how to estimate the MLE for $\lambda$ for given samples of a random variable. I have been using the 'boxcox' function in R for a sample of a ...
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1answer
25 views

What do the coefficients of the crossproduct of regression mean?

How can I interpret the coefficients of the crossproduct of each of the following codes? What do they mean? How can I deduce that they correspond to our expectation? ...
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101 views

Efficiency of beta estimates with heteroscedasticity

I need something clarified and that is when you have non-constant variance, estimates won't be biased but will be a problem when it comes to the S.E. formulas and efficiency. Therefore OLS estimates ...
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How to test for mediation with a continuous mediator and DV, but a categorical predictor?

I want to explore whether attitudes mediate the relationship between employment status and intention to apply to graduate school. (See image below). I planned to use the Sobel Test to explore the ...
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1answer
26 views

Observations with very high or very low residuals in regression

If a regression model is applied and there exist residuals that is very high or very low (meaning outliers compared to the others), is it good practice to get rid of those observations and then do the ...
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27 views

Forecasting after Box-Cox transformation

I did a regression and found that my residuals pointed out that my data is heteroscedastic. I applied the Box-Cox transformation and my new model looks as follows, ...
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2answers
17 views

Percent error for linear regression model

Suppose I fit a linear regression $y = \beta x + \rm error$. In this situation, $x > 0$, $\alpha > 0$, and therefore $y > 0$. Moreover, the $\rm error$ is normally distributed with mean $0$ ...
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14 views

Model matrix of a mixed model

Suppose I have a mixed model like this: ...
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23 views

Plot and interpret ordinal logistic regression

I have a ordinal dependendent variable, easiness, that ranges from 1 (not easy) to 5 (very easy). Increases in the values of the independent factors are associated with an increased easiness rating. ...
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25 views

Is segmented (piecewise) regression possible with a dichotomous dependent variable?

I have created a model of American cities with a dichotomous Y variable using logistic regression. I have theoretical reasons to believe that the model will differ significantly between larger and ...
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data representation with nominal, ordinal and continuous variables

Suppose I have data of this format: customer, country, location, unit price (discrete set), traffic, etc. (more nominal/ordinal variables) I want to know how country affects unit price, how do I go ...
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27 views

Trouble fitting a simple linear regression

I have been trying to do a simple linear regression of x3=Weeks Claimed against x4=Weeks compensated. I am having problems because my residual standard error is very high and also my residuals are ...
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1answer
54 views

Remove effect of a factor on continuous proportion data using regression in R

I have a data set of continuous proportions which depend on a fixed-effect factor, e.g.: ...
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1answer
15 views

How to interpret results if a reference category of a categorical variable in multivariable logistic regression is not significant?

I am trying to do a multivariable logistic regression and using a normal binomial logistic regression, using binomial variable X (coded ...
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1answer
16 views

How to find correlation among dependent variables?

If I want to find how strongly a dependent variable is related to another dependent variables in a study, do I make use of multiple regression? The reason I am asking is because the book mentions ...
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3answers
102 views

In simple linear regression, what is the covariance between the error term and the residual?

In simple linear regression, what is the covariance between the error term and the residual? Model: $y_i = \beta_0 +\beta_1 x_i + \varepsilon_i$ What will be the $\rm {cov}(\varepsilon_i,\ e_i)$, ...
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1answer
40 views

lm() function in R

This is kind of a follow-up question from this post: Gradient descent vs lm() function in R? Is there any literature available for the QR decomposition concept involved in the ...
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Correlation & Regression Prediction [on hold]

I have a homework question. I have solved most of it already, but am unsure how to proceed with one specific part that involves prediction (Parts B & C). I am not looking for anyone to just give ...
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48 views

Linear Regression Real Life Example

I am learning Machine Learning(Linear Regression) from Prof. Andrew's lecture. While listening when to use normal equation vs gradient descent, he says when our features number is very high(like 10E6) ...
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1answer
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Correlating two questionnaires with grouped items

I need to correlate employee engagement (gathered data using the 9 item UWES questionnaire) and organizational commitment (gathered data using the 18 item Organizational Commitment Scale). The both ...
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2answers
35 views

Is there any tool that can do Vector ARIMA modeling in time series

Vector ARIMA model is used in multiple time series analysis. I am just wondering if there is any software or tool can be used to build the model. Some tools,like R, can only be used to predict the ...
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2answers
96 views

How to interpret insignificant categorical variables for logistic regression

I am trying to interpret categorical variables with more than two classes. Some are significant whilst other classes are not. What can I infer from the insignificant ones? Does this mean the ...
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What analysis do I need to run? [on hold]

I have a predictor with responses from 140 people in group A and 60 in group B. My mediator only uses responses from group ...
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Testing the quality simple linear regression model

I have made a simple linear regression model based on two sets of monthly data from 1960 to 2008, using only data from 1960 to 2000. I was now wondering how I would go about back-testing this model ...
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1answer
42 views

Building a time series model using more than independent variables

I am working on a project, and I am totally new to statistics. I have sales data for last two years at week level, along with other variables like temperature, holiday (TRUE/FALSE), where holiday are ...
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49 views

Choosing the appropriate method to determine risk factor (logistic regression)

My question is about logistic regression, and I want you to advise me to use the appropriate method for my problem. Here is the description: My goal is to determine the risk factors for a disease (a ...
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22 views

Non-normal observations in regression modelling [duplicate]

I read an article that says the dependent variables in a regression model must be normally distributed. The way i understand it, is that the observations for the regression model must then be normally ...
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26 views

Inflation as an independent variable

Assume a model like this, basically explaining stock market returns with a bunch of stuff: ...
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1answer
35 views

Using results of regression on raw observation values to approximate results of regression on relative change between observations (Simple, Linear)

this is my first time on Stack Exchange so if I did something wrong please tell me. I have a time series dataset. There is an observation $(y,x)$ for each continuous time $t$. Let’s say for each day ...
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6 views

How to extract long run and short run coefficients from ARDL (UECM) estimates?

I have estimated ARDL(UECM) in eviews but I dont know how to specify or extract the long run an short run estimates/coefficienst? what is the standard procedure to do so?
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28 views

What is the code for cubic spline regression model in SAS

I ran an experiment that identified lame and non-lame cows every day for 325 days from a pool of 936 cows in one herd. At the same time, I collected data on various variables like milk volume, fat and ...
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21 views

How to subset alternatives in nested multinomial logistic regression?

I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...