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

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Does Stationarity for Time Series extend to Independent Variables?

There have been many questions about the importance of stationarity and also its means of calculation here on CV, but one question that I have not seen an answer to is whether or not stationarity (in ...
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0answers
12 views

Why does the SSR have 1 degree of freedom in simple linear regression?

I understand degrees of freedom as the number of things that can independently change. And typically, in coming up with the degrees of freedom, if you have n terms, then you just subtract out the ...
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10 views

Spatio-temporal data [on hold]

I am an italian student, and I'm looking for a particular dataset. I'm interested in a model for spatial regression, with time-varying data. I'm looking for data with coordinates, measured in ...
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8 views

Live selection of movie to suggest based on similarity of users

I am working with movie selection for users. 1 ) One of the first ways I thought was taking all the clicked only movie data and building decision trees out of it. Then when input is passed, the ...
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1answer
30 views

LR test on marginal effect

Say I have the following regression model: $$\text{Wage}_i = constant + α·\text{YearsOfEduc}_i + β·\text{Age}_i + γ·\text{CompletedHighSchool}_i + \mbox{δ·$\text{NumOfSiblings}_i$} + ...
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31 views

regression for binary classification

Given a binary classification problem, is there any inherent difference (or advantage) to using a classifier (say a logistic regression) and a regression, where the classes are denoted by 0 and 1 (or ...
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1answer
19 views

Finding multinomial logit regression coefficients in R

I run a multinomial logit regression model for a multiclass classification problem and use the following R function: trainedModel <- multinom(UNS ~.,data=traindata) Where UNS is the target ...
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1answer
8 views

Pretest posttest regression

I am trying to set up a multiple regression for a pretest posttest dependent variable. There will be no control group, and we will be controlling for age (continuous) and gender. Want to use the ...
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7 views

Plotting fraction of NAs of a data frame [migrated]

Does anyone know how to plot the graphs of figure 23.1 of the example chapter of Steyerberg's book? The R-function is called "na.plot2" and Displays for example the fraction of missing values in data ...
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2answers
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Regression problem without complete data set

I have a medium sized database of hands played at an online poker website. In poker, you starting hand can be classified into one of 169 different hole card combinations (e.g. AA , 87s which means ...
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1answer
41 views

Can multiple logistic regression be performed without a reference/baseline?

I was wondering of it's possible to perform a multiple logistic regression without a baseline reference. The analysis I'm dealing with doesn't have a "natural" baseline reference. Thanks in advance
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1answer
15 views

how to estimate heterogeneous effects?

I have a dataset where I run regression discontinuity with the following code: xi: reg work post i.post|m i.post|m2 age age2 age3 immig primary hsgrad univ sib pleave i.q if m>-10 & m<9, ...
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31 views

Regression discontinuity

I am analyzing some Stata code for a regression discontinuity analysis. The results of this analysis are presented in table 5 of the Online appendix to “The Effects of a Universal Child Benefit...”. ...
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1answer
25 views

Wald test on marginal effect

Say I have the following regression equation: $$Wage_i = YearsOfEduc_i + Age_i + NumOfSiblings_i + u_i$$ How would I go about peforming a wald test of the hypothesis that for an individual with ...
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11 views

About Hypothesis Test In Spatial Regression

I'm doing estimation of spatial lag/error model using R package "spreg"/"spdep". But I can't find any method to do hypothesis test after regression. For example, I want to test whether two ...
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11 views

Interpreting interactions in logistic regression output [duplicate]

Using chi-square analysis, I find significant p-values for age (as a continuous predictor variable) and presence of a hip fracture (as a dichotomous categorical predictor variable) for the occurrence ...
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33 views

R: Prediction using glm() [migrated]

I am using glm() function in R with link= log to fit my model. I read on various websites that fitted() returns the value which we can compare with the original data as compared to the predict(). I ...
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0answers
19 views

Chi-squared test and logistic regression

Is there a relation between chi-squared test and logistic regression model in a similar manner between ANOVA and linear regression?
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1answer
27 views

Linear Regression Percentage Increase/Decrease

I am trying to find out a way to display the percentage increase or decrease to my customers using y = mx + b ...
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3answers
46 views

Simulation from linear model with additional variables

I want to test the performance of a variable selection method in linear regression with normal errors using simulated data: $${\bf y}= {\bf X}{\bf \beta} + \epsilon,$$ where, as usual, ${\bf y}$ is ...
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34 views

R- Improving linear regression fit

I am trying to construct a predictive model in R. I am using the glm() in R to fit the model. I am getting a very high residual error after fitting the model. My target values are in the range of ...
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0answers
32 views

Determine if regression results are significantly better with method A or method B

I'm working on a regression case and I am using two methods, lets say method A and B. Due to the randomness in the optimisation techniques of these methods the output will always differ slightly. ...
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0answers
6 views

regression test or two bloc PLS model to prove a gene expression matrix relationship

I have two gene expression matrices, matrix A coming from a set of two hypothetically different cells while matrix B is coming (for certain) from only one of them. The structure of a gene expression ...
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12 views

Need to transform data before running mediation/model with bootstrapping (PROCESS)?

I am reading through Hayes' book on mediation and moderation analysis (2013) which describes the PROCESS macro he created to use bootstrapping in order to arrive to confidence intervals to check the ...
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10 views

Managing/maintaining multiple models

Sorry for posting a vague problem statement, but this is very practical issue i am facing right now and couldn't any hint/solution. My use case is that while trying to build regression model, there ...
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19 views

Detecting a step change in time ordered data

Suppose I have data which looks like this: ...
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2answers
19 views

Regression produces a high coefficient of determination, but also a high MSE

I've ran several regression models on a dataset (the SEER cancer dataset). I'm trying to use regression to calculate how many months a cancer patient can expect to live. Each record consists of around ...
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Comparing the results of 2 employee surveys that used different scale lengths

Is it possible through some form of linear regression to compare the results of two different surveys (same questions) that used two different likert scale lengths (i.e. 6-point = Strongly Disagree, ...
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2answers
25 views

Proving Linear Estimator (beta) is BLUE?

In the book Statistical Inference pg 570 of pdf, There's a derivation on how a linear estimator can be proven to be BLUE. I got all the way up to 11.3.18 and then the next part stuck me. After ...
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0answers
14 views

How big is the risk for regression in a single arm meta-analysis?

I'm performing a single arm meta-analysis of continous data deriving from efficacy evaluation of control gorups surgical procedure. How big is the risk for regression to the mean? And How it could ...
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1answer
40 views

Algorithm to find subsets with high correlation

I have a reasonably large dataset (d) with predictor variables x1...xn and a target variable y. I can use recursive partitioning (such as CART or rpart in R) to find subsets of d with a high (or low) ...
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1answer
28 views

Can binning a continuous predictor or DV variable improve large data sets fit?

I read that averaging and binning a continuous predictor variable is in general a bad idea because it's always better to fit the continuous relationship through splines, poly and all of that. Sure, I ...
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2answers
73 views

Rate of change for the regression model $Y^{\frac{1}{2}}=a+b_1*log(X_1)+b_2*X_2^{\frac{1}{2}}$

Hello I have the regression model $Y^{\frac{1}{2}}=a+b_1*log(X_1)+b_2*X_2^{\frac{1}{2}}$ which works very well however I am trying to interpret it in terms of change for each different $X_i$ term. I ...
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1answer
14 views

Rank deficiency in polynomial trend analysis

I am currently trying to fit a model for some reaction time data from an experiment with four consecutive blocks of the same task. I am interested whether there is something like an effect of practice ...
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2answers
198 views

Absolute beginner needs help with correlation

I am very new to statistics, and have searched around the net and stack exchange for an answer, and have tried to guess how to deal with the problem. Therefore this post. I hope someone can help... I ...
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41 views

Confidence interval and confidence band

How are confidence intervals related to the confidence band (in a nonlinear regression problem)? I understand that the term confidence interval is reserved for the parameters involved in a regression ...
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0answers
10 views

Missing value replacement in modeling and scoring

Here I have two questions I build a logistic regression model. While building model I have few observations have NA values, so I replace with mean value. Model is looking good and when we tried to ...
4
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1answer
118 views

Back transforming regression results when modeling log(y)

I'm fitting a regression on the $\log(y)$. Is it valid to back transform point estimates (and confidence/prediction intervals) by exponentiation? I don't believe so, since $E[f(X)] \ne f(E[X])$ but ...
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28 views

Can I Calculate the MSE for a Linear Regression Model using a Bootstrap?

I'm currently reading the book, An Introduction to Statistical Learning, and I'm struggling a little with the bootstrap approach. As far as I understand, I can use a bootstrap in almost all situations ...
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1answer
33 views

adjustment of covariates in linear model

I am trying to understand the adjustment of covariates in the linear model such as multiple logistic regression. How does adding a covariate adjusts the coefficients for that covariate (any intuitive ...
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13 views

How can I get the pseudo-R squared by using censreg (tobit regression)?

I was using VGAM for tobit regression but when I entered new dataset which had more than 50000 records, it got errors like this: ...
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1answer
72 views

How can you prove that the naive estimator is less efficient than the OLS estimator

The "naive estimator" is an estimate of the slope obtained by joining the first and last observations and dividing the increase in the height by the horizontal distance between them. Given that the ...
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7 views

Dealing with numbers-based categorial data in rf regression: to standardize, or encode?

I'm working with the SEER cancer dataset, and I'm trying to use regression to calculate the months a breast cancer patient can expect to survive given certain variables. Some of these variables are ...
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0answers
11 views

Gaussian Processes: 2-output [latitude longitude] as regression output

I'm trying to model a problem where inputs are 100-d vectors and outputs are 2-d vector [latitude, longitude]. I need to perform prediction on new unseen 100-d vectors and find out the latitude and ...
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1answer
28 views

Saving each step of Backward selection in R

I'm trying to recreate Leo Breiman's work http://www.stat.washington.edu/courses/stat527/s13/readings/BreimanSpector_1992.pdf and I'm experiencing some major difficulties in R. I've made it that far ...
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20 views

Comparing regression models, same and different response variables [duplicate]

My basic question is how to compare regresion models with (1) the same and (2) different response variables. My data include the following variables: x: dosage, 10 levels y_meas: lab measaured ...
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1answer
79 views

Predictive Modelling in R

I am new to R and I am trying to do some predictive modelling on data set which has 16 feature variables and the target value is numeric in R. I am not sure if the steps I am following will help me to ...
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0answers
8 views

Kernels determination in Gaussian Regression multiple input features

How can i choose a proper kernel for Gaussian Regression when i have more than one feature in my inputs? I am relatively new to this and all the lectures and most literature seem to have described ...
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0answers
34 views

Using a mixed effects regression model for between-subject design?

I have data from a between-subject experiment, where every subject was assigned to one of the two conditions, and completed varying number of trials (as much as they wanted). Number of trials is ...
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0answers
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Poisson regression

I'm analyzing an article for my studies with the hypothesis if a change in work motivation is related with a change in mental well-being (http://www.sciencedirect.com/science...01879113001541). Sadly ...