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

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5 views

Fixed Effects vs Lagged DV vs. First Differences Regression

What are the differences between using unit fixed effects, unit fixed effects and time fixed effects, lagged DV, or first differences to analyze a time series with 4-5 time periods and 35-50 units per ...
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0answers
11 views

Can Random Forest be used for Feature Selection in Multiple Linear Regression?

Since RF can handle non-linearity but can't provide coefficients, would it be wise to use Random Forest to gather the most important Features and then plug those features into a Multiple Linear ...
2
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9 views

Linear regression with prior on $\arctan \beta_1$

Suppose we have $\hat{y} = \beta_1 x + \beta_0$ (I ask only for the univariate case.) A typical Bayesian approach might involve Normal priors on both parameters. I was thinking today about a ...
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0answers
4 views

class is intervalar 0- 20 regression or NN?

The class is quantity of children. So at first I thought of a linear regression, but then, since it will never predict extreme values, but there will be lot's of zeros. Is there any problem of using a ...
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1answer
22 views

Find a best fit curve for a function f(x) = g(x+1)/g(x)-g(x+1)

I have a set of noisy data that can be described by a functional form. For each observation y(x), where x is an index that runs from 0-100, I know that y(x)=f(x+1)/f(x)-f(x+1). I would like to find a ...
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1answer
23 views

Logistic regression is appropriate? Forecasting player’s serve point win % as a binary variable, w/ both numeric and categorical independent variables

I effectively want to model the probability of a player winning his service point (a point in which he is the server) based on the values of explanatory variables (namely court surface and opponent ...
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1answer
21 views

why in logistic regression the probability mass equal the count

It's said that logistic regression is well calibrated and preserves marginal probability. What does that mean? Thanks.
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12answers
682 views

Why would parametric statistics ever be preferred over nonparametric?

This may be a stupid question but it's been bugging me for years. Can someone explain to me why would anyone choose a parametric over a nonparametric statistical method for hypothesis testing or ...
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7 views

coding for multinomial logistic regression dv

I have run a multinomial logistic regression. One of the 3 IVs is categorical and has 5 levels and the one DV is categorical and has 6 levels. I coded the levels from 1-5 for the IV and 1-6 for the ...
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6 views

Linear Regression vs Single Layer Perceptron [duplicate]

What is the difference between a linear regression and a single layer perceptron, as their mathematical expressions are the same?
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21 views

Running repeated cross-validation for multiple models using same dataset (caret package)

I'm currently using the train() function in the caret package to run 10-fold repeated cv on a random forest model. I would also like to explore other statistical and machine learning models for use ...
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11 views

Exp(b) in multivariate Cox regression

I am trying to interpret the results of a Cox regression. I ran a multiple Cox regression analysis of an categorical variable—heart rate including 5 levels. I added covariates that were also ...
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1answer
29 views

When there is only one dependent variable, is partial least squares regression the same as principal component regression?

When there is only one response (dependent) variable, what is the advantage of partial least squares (PLS) regression over principal component regression (PCR)? My understanding is that PLS is only ...
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15 views

Analytic (inverse sampling variance) weight in stata

I have a question about using aweight in regression in Stata. I have school level data (mostly percentages) but I want also to take school size into consideration. ...
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0answers
6 views

Interpretation of standardized beta coefficient estimates and use within the exponential formula for prediction purposes

I'm working on a data set where I plan to use logistic regression to evaluate non-random habitat selection for a wildlife species. My dependent variable is 1 = used location by an animal and 0 = ...
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1answer
35 views

Linear regression with sine/cosine elements

How can you derive formula and regression coefficients for a regression model of a form $y(x)= A + B\, x + C\, \cos (2 \pi x) + D\, \sin (2 \pi x)$? I know that there are automatic tools who can do ...
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1answer
33 views

Logistic Regression modeling in R

Consider this model: $Y_i$ ~ Bernoulli($\pi_i$) $X_i$ = 0,1 logit($\pi_i$) = $\lambda^{X_i}$ * $\beta_0$ This model simplifies to logit($\pi_i$) = $\beta_0$ , when $x_i=0$ , and logit($\pi_i$) = ...
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3 views

Does the cvglm function in boot package have arguments for mean centering and normalizing?

Does the cvglm function in boot package have arguments for mean centering and normalizing? If not, how can I run k-fold cross validation with mean centering and normalizing in R ?(especially for ...
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1answer
20 views

Whether to apply the logit transformation to proportional predictor variables in a multiple linear regression? [including proportions of 0.0%]

In a linear regression, I have a number of predictors variables that are expressed as proportions. The outcome variable is continuous. My residuals are not normally distributed, with a mild to ...
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13 views

Visualizing multi-class ROC analysis [duplicate]

I am running a multinomial logistic regression model (with 3 possible outcomes) in R. I am trying to find the best way to assess the predictive power/accuracy of the model, and the best thing I've ...
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0answers
20 views

Root-Mean Squared Error for Bayesian Regression Models

I'm trying to get a sense of my prediction errors for a Bayesian regression model and I was using the Root-Mean-Squared Error. My question is, since are predictions are stochastic, would it make ...
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1answer
29 views

How does one treat censored data in SAS?

I have some censored data and I'm not sure how to deal with it in my regression analysis. The study was not a time series and all examples I've seen in SAS have been in the context of survival ...
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0answers
11 views

Estimating a gravity Modell Stata [on hold]

I am trying to estimate a gravity modell for trade analysis. My dataset contains 219,573 observations from 1948-1997. I tried xtset to get an overview about how balanced the panel actually is.. My ...
0
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1answer
42 views

regression with ratio variables

I plan do run a regression analysis with ratio defined variables such as (FX loans/ total loans, tangible assets/total assets etc.) and I have only 13 annual observations. This regression is needed to ...
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0answers
25 views

What is the difference between Fisher's regression and Durbin & Watson's regression?

What is the difference between Fisher's regression and Durbin & Watson's regression? Durbin & Watson suggested the error terms are unobserved. Is this important?
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1answer
28 views

Online linear regression. Possible or not? [duplicate]

I don't have a strong background in statistics, but I'm a programmer and needed to implement some statistical aggregate functions in the DSL I'm writing. This DSL processes events in an online ...
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26 views

Best way to model this data, qfit or fpfit? How to get equation?

So I have this relationship, which is obviously not linear. The purpose is to see if there is (and what kind of) a relationship between FRAG (test score) and MD-R (mm^2/s). There are other covariates ...
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13 views

Significant interactions force main effects to be insignificant and plus change their sign--how to interpret? [duplicate]

I've read through many similar posts regarding significant interaction wiping out the significance of main effects, but since there were no questions regarding changing signs I decided to post another ...
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13 views

What type of panel regression is this

For the following equation $$ Y_{ct} = \alpha_c^D - \phi i_{ct} + \eta logx_{ct} + \epsilon_t^D + \epsilon_{ct}^D $$ where, for country c at time t, $$ Y_{ct} \text{ is the log real GDP}\ $$ ...
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1answer
12 views

Extracting regression coefficients [on hold]

Is there a way to extract the regression coefficients in order to plot them? Right now, we have a process where we run these in Matlab and then export the coefficients to Excel where we then chart the ...
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0answers
7 views

Fractional Response variable

I have a fractional response variable Y=X1/X2 where X1 is one of the constituents of X2. I want to model Y as a function of X2 and some other categorical variables. But since X2 ,in principle, lies ...
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6 views

non significance of variables in my VAR estimate

I am running a VAR model with 7 variables, but less than 10 out of 49 independent variables are significance. What could be the problem please?
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31 views

Power of a Interaction term in R

I have analysed a dataset with a linear regression model, including an interaction term between a binary variable and a continuous variable. The interaction was significant. Afterwards, I have fitted ...
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9 views

Beta Coefficient and correlataion [duplicate]

What is the interpretation of negative Beta coefficient with positive correlation? TNX
2
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1answer
71 views

Nagelkerke value equals 1. Why?

I have run a logistic regression model, which leads to acceptable results (e.g., McFadden's R2 >10%). However, the Nagelkerke value is always 1, which seems like a failure to me (using the comand ...
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18 views

Structural Break - Stata

I have used Stata to run a time series multiple regression. I know that there is in fact a structural break in the data and the point at which it occurs; therefore, I have estimated the regression ...
0
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1answer
73 views

When to not use R squared [duplicate]

I recently graduated graduate school and am looking for a proof on R squared. Specifically when to not use it. I really remember a professor impressing upon me multiple times not to report R squared ...
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2answers
80 views

Why is linear regression different from PCA?

I am taking Andrew Ng's Machine Learning class on Coursera and in the below slide he distinguishes principal component analysis (PCA) from Linear Regression. He says that in Linear Regression, we ...
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0answers
9 views

How can I ENTER a 4-way interaction in a hierarchical regression blocks in SPSS? [on hold]

I have 4 variables, and I want to compute their interaction in a hierarchical multiple regression. But I do not know how I put main and interaction of variables in blocks of hierarchical multiple ...
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1answer
52 views

Does one need to transform percentages/proportions for a multiple linear regression?

I am aware that one should transform percentages and proportions when using them in an ANOVA, due to the values being bounded by 0 and 1. I have seen suggestions that the best transformations are ...
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0answers
28 views

Interpretation of R-squared when using FGLS

Context: I am analyzing time series and cross-sectional data using Stata's xtpcse command which corrects for autocorrelation in panel data using a Prais–Winsten ...
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0answers
26 views

K-fold cross validation [on hold]

I'm working on a data set that contains used (value= 1; animal locations) and random locations (value = 0). I'm using logistic regression to assess non-random habitat selection. I have 6 continuous ...
0
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0answers
10 views

Adding Regression Lines to Multiple Scatter Plots [migrated]

Had a look around and couldn't find an answer to my question, so finally stopped lurking. I've been creating multiple scatter plots comparing each column to the others I used the script attach(...
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0answers
12 views

Multinomial logistic regression, how to treat conditions without variance?

Currently I need to conduct a multinomial logistic regression, but my output shows an error message and incomplete results. I expect this is due to the fact that in one of my conditions, all ...
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0answers
22 views

Classifier that learns provided by only positive examples?

I was wondering if any of you has ever worked with classification/regression using only positive examples (one class). I would need such a system. The basic idea is that it is going to accurately ...
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2answers
400 views

what does linear regression actually mean?

Wikipedia gives the following definition for linear regression: In statistics, linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or ...
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0answers
20 views

K-fold cross validation dealing with an interaction term

I'm working on a logistic regression analysis and have a data set that contains ~12,000 data values (~6,000 values = 1; ~6,000 values = 0). I would like to use a k-fold cross validation process to ...
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0answers
31 views

Tennis Analytics: How to Build Model Predicting Player Service Point Win %

I have collected a large amount of tennis match data including player names, court surface, player ranking points at time of match, handedness of player, point by point breakdown of match etc. I ...
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9 views

What's a good robust approach to something like multi-variable local polynomial regression with known changing noise magnitude?

I have a sample-based estimator of a function $f(x,y)$ parametrized by two inputs. The region of valid $x$ and $y$ is an axis-aligned (bounded) rectangle. I have decided to create a grid of points in ...
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1answer
37 views

Comparing regression models with different coding of the same linear predictor

How can I determine whether one coding of a linear predictor leads to a better fit of the corresponding regression model than the other? In the following example, the restricted cubic spline coding of ...