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

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Determining whether a successive instances are conditional or independent

I hope I can appropriately describe the problem. I have an example data set with 610 individuals with made up analogy (it's not really about cars). I want to determine the number of people have x ...
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5 views

Repeated Observations Due to Pairings in Logistic Regression

I have data with repeated observations within a given year. Here's a snippet of the data: ...
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21 views

If $\operatorname{Var}\left(\varepsilon\right) = h\left(X\right) \neq \sigma^2$, what can we know about $\operatorname{Var}\left(\hat{\beta}\right)$?

This question uses the derivations found here. Notation Assume: $Y_i=\beta X_i + \epsilon_i$ for random variables $Y_i$ and $\epsilon_i$ $\operatorname{E}\left(\epsilon_i\,|,X_i\right)=0$ so that ...
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16 views

Undergrad linear regression topic [on hold]

I have to prepare a mulitlinear regression research paper with cross-section data. I thought doing something on the credit ratings of sovereign debt (of one of the Big3 CRAs) or something similar. ...
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13 views

How to deal with factors with rare levels in cross-validation?

Suppose in a regression analysis in R, I have a factor type independent variable with 3 levels in my train dataset. But in the test data set that same factor variable has 5 levels. Therefore I can not ...
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29 views

Maximum likelihood method vs. least squares method

What is the main difference between maximum likelihood estimation (MLE) vs. least squares estimaton (LSE) ? Why can't we use MLE for predicting $y$ values in linear regression and vice versa? Any ...
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6 views

F test in random effects panel regression

I'm using random effects panel regression and I've 3 covariates not statistically significant and I want to test if the three parameters associated with those covariates are jointly equal to 0. Could ...
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10 views

How to test for interactions of continuous measure with two repeated-measures factors in R?

I am doing an items analysis of difficulty ratings of a large set of math problems which were constructed to represent the factorial combinations of two binary factors, feature1 and feature2. The ...
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1answer
31 views

2SLS probit vs LPM

I am using 2SLS to estimate the effect of education on the probability that one works. In the first stage I regress education on my instrument and the other exogenous control variables. The same ...
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10 views

Correction of data using a correlation

Suppose I have measured the outcome variable A using a (psychophysical) test that determines the ability of a subject to discriminate between two stimuli with a certain difference (the variable X). It ...
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1answer
24 views

Measuring impact of advertising on retail sales

I have a dataset of retail products which contains weekly sales for 12 different items in a single category. For each item, I have three dummy variables representing different types of advertising ...
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38 views

Difficulty plotting regression in R

I am trying to plot a regression using plot() and keep getting the error message "Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ". ...
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15 views

Multilevel models benefits vs. separate group models

What are the benefits of multilevel models vs. running a separate model for each group? My understanding is that MLM offer a method to effectively model interactions against all the base predictors. ...
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39 views

Assessing the need for random effects terms

During the model selection phase for mixed models, there are typically several possibilities to choose from; in fact, the number of possibilities is increasing in the number of covariates used. How ...
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21 views

When adjusting for X1, have we adjusted for X2, to the extent that X2 is related to X1?

I've just read Elizabeth Stuart's paper on matching methods (http://biostat.jhsph.edu/~estuart/Stuart10.StatSci.pdf), which I find very informative. She discusses propensity score methods and the ...
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1answer
28 views

Help with analyzing/planning a physical experiment — regression

This is a real experiment about to be performed Batches of samples will be prepared. A Striker will be used to see if a reaction will occur. For example: 20 drops might be performed, and number of ...
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I have data independent variable scoring 1 to 4 and a dependent variable number of people dependent variable,,,,,Which regression or model i prefer [on hold]

Access to water , Road , Sanitation, parks etc 1=25% have access 2=50% have access 3=75% have access 4= >75% have access Dependent Variable Number of people in a particular area... Which model or ...
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29 views

Analyzing ordered factor vs continuous variable

I have data of 50 students of a class as follows: build : an ordered factor with levels 'low', 'medium' and 'high' score : a continuous variable (values 1-9) ...
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13 views

what could be the best method to find best scenario based on revenue(statistical analysis) in python?

I have a data set on which I want to do some statistical analysis. The sample data set is in a csv file and of following nature: ...
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9 views

MSE of training set and validation set for linear regression

The wikipedia article on cross validation http://en.wikipedia.org/wiki/Cross-validation_(statistics) makes the claim that "under mild assumptions that the expected value of the MSE for the training ...
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19 views

Can I mix data and do a regression and/or can I sum multiple regression formulas for a 'master' formula? [on hold]

I need to make a formula for the line of best fit (trendline) for multiple regressions, (and I'm working with a college-level statistics knowledge so please forgive my ignorance). The data I will be ...
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8 views

Standardized Regression Coefficients for categorical interactions: lm.beta() vs. regressing standardized variables

I am working with a regression model from which I would like to compute standardized regression coefficients. I am writing primarily regarding an observed discrepancy between coefficients obtained by ...
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15 views

Maximum number of alternatives in a discrete choice model

We are modeling a discrete choice scenario, with alternative-specific coefficients. We also break the assumption of independence of irrelevant alternatives. To model this, we are using an ...
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1answer
43 views

What is the significance of a linear dependency in a polynomial regression?

I'm trying to find the best polynomial regression for a dataset where the polynomial's power is between 2 and 10. So the regression can have an x10 term at most in it. The dataset itself is simply a ...
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9 views

Can you regress index valued variables with variables (actual numbers)?

I am doing my dissertation and looking at the impact of education on economic growth. I will be carrying out Panel data regression on certain variables to see how this impacts Economic Growth (GDP per ...
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1answer
32 views

Preventing overfitting with Least Squares Linear Regression via QR decomposition

I am trying to solve a linear regression problem in an automated fashion, however am having a problem with extremely large weights. I have several thousand datasets, and am running linear regression ...
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16 views

How does one interpret a demeaned log interaction term?

I am having problems interpreting my regression equation. I want to know the effect of an increase in variable $x$ on $y$ for different values of $z$, but as it's in logs and the interaction term is ...
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39 views

Can bootstrap re-sampling be a re-sample of a smaller size

i am attempting to run a smaller instance of my regression panel data , because it is a pretty huge regression (Fixed effect, heckman selection) and it takes 4 hours to run every time. I am ...
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7 views

Question about a control variable for ''progressitivity measures (Taxes)'' (economics and econometrics)

Can anyone explain to me what this sentence means econometrically? I mean what I am supposed to do in order to conclude to one control variable (time series). ''The progressivity measures are obtained ...
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1answer
29 views

How to find the long-run relationship using this regression (3rd time posted)

I know this is unorthodox but the exam is in 15 hours and if a question like this turns up I'll be unable to answer it. I've posted this twice already, the first time it was put on hold and the second ...
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6 views

Problem Using leaps() code in R [migrated]

In my case, the data consisted of 8 variables and 500 observations. When I used the leaps() code, instead of showing the $2^8 - 1$ submodels, the output showed only ...
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10 views

Analyzing whether several categorical variables might have a causal relationship with a dependent variable

I am trying to use some data to assess why certain terrorist organizations claim responsibility for their attacks and why sometimes they don't. I have a data set that contains relevant information so ...
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10 views

relation within Gauss-Newton method for minimization

If we study model fit on a nonlinear regression model $Y_i=f(z_i,\theta)+\epsilon_i$, $i=1,...,n$, and in the Gauss-Newton method, the update on the parameter $\theta$ from step $t$ to $t+1$ is to ...
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1answer
50 views

Simple question on odds ratios interpretation

I am trying to interpret the Odds Ratios (ORs) from a multiple logistic regression model that compares the performance of various clinics in terms of preterm birth rate (measured as "Yes/No preterm ...
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36 views

OLS with ordinal dependent variable - do the coefficients mean anything?

I currently read a paper in which the author has asked people 3 different questions regarding their life satisfaction, all of which are to be rated on a four point scale: 1) very low, 2) low, 3) high, ...
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2answers
33 views

Doing multiple regression without intercept in R (without changing data dimensions)

I am trying to calculate multiple regression in R without intercept. My data is as follow: ...
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22 views

which test should I apply to find which model is significantly different? [on hold]

I have two questions 1- regression I have performed many regression models (10 models) and therefore, I have 10 prediction columns and one column or more for my real data (independent variables) ...
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2answers
37 views

multiple linear regression with interactive categorical variables

I want to include in a multiple linear regression model, the interaction between categorical variables. I have three categorical variables: CO2 (0,1) Temperature (0,1) Soil (1,2,3) But when i ...
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1answer
144 views

When to use Log in Regression?

I saw this sentence: "I use log(income) partly because of skewness in this variable but also because income is better considered on a multiplicative rather than additive scale. In other words, ...
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1answer
24 views

Coefficient Decreases but Standard Errors stay the Same with Inclusion of Control Variables

I estimate 2 models in OLS. $Y=\beta X+e$ and $Y=\beta X+\gamma W +u$ The inclusion of the $W$ variable decreases the size of $\beta$ but does not change the $Var(\beta)$. $X$ and $W$ are not very ...
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1answer
30 views

How could the predictive mean in a GP become negative when both the prior and the training target values are non-negative?

I am training a Gaussian process regression where the training target values are between 0 and 1 and the prior mean is the fixed zero function. The predictive mean sometimes becomes negative e.g. ...
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19 views

Working on my dissertation, and need to figure out whether to use MANOVA, MANCOVA, Multiple regression, or multivariate regression

I am working on my dissertation, and I am having a hard time choosing a statistical model to follow. I am using an existing dataset. The results of the dataset are self-reported. There are more than ...
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1answer
82 views

Why $y_i$ becomes $(y_i-\overline y)$ in linear regression

Trying to figure out why $y_i$ becomes $(y_i-\overline y)$ in the below expression for finding $\widehat{\beta}$. Any help is highly appreciated.
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1answer
47 views

How to calculate likelihood of linear regression

This is a pretty basic question, but one I am having a hard time finding an answer to. How do you calculate the likelihood of a simple linear model? Like, say, $$y=\beta_0+\beta_1x+e$$ I am working on ...
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24 views

Relationship between the parameters of the Normal distribution and parameters in the probit with multiple predictors?

According to A. Agresti (2007, p. 73) in binary probit regression: "The parameters of the normal distribution relate to the parameters in the probit by mean (mu = -alpha/beta) and standard deviation ...
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9 views

Approaches for multivariate nonlinear (but parametric) regression?

I have some data that is nonlinear, but is curvilinear. It is two factors and a dependent variable. Each factor has a pretty good fit when applying a growth curve when compared against (this is ...
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1answer
22 views

Weighted GLM without weights

Suppose we have at our disposal a glm() that's got all the typical features except the ability to specify weights. Intuitively, I can trick it into using weights ...
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32 views

Using multiple regression to predict x values

I understand the basics of running regression. I have used it in the past to create predictor values for engineering problems. For instance, how much cooling does a system need if previous systems ...
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0answers
9 views

how to specify range of lag in prewhiten CCF using package TSA in R

I am doing time series regression using package TSA in R. I have 2 time series, say x and y, so I started by doing prewhitened CCF. So, 2 issues I have encountered and would really appreciate if any ...
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Reverse-engineering a (custom goods) pricing algorithm - each db row has: | 3 factors | 2 co-variates | price | (I have over 100k rows of data) [on hold]

just wanted to mention up front that my question doesn't concern dynamic pricing, price optimization, revenue management, etc. No time series analysis either. It's just a simple multivariable ...