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

learn more… | top users | synonyms (1)

1
vote
0answers
7 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 ...
1
vote
1answer
23 views

Algoithm 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) ...
1
vote
1answer
20 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 ...
0
votes
1answer
45 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 ...
0
votes
1answer
8 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 ...
1
vote
2answers
183 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 ...
0
votes
0answers
19 views

how to interpret and improve this regression result

I used a linear regression in order to predict a life time value per customer .I ploted the the customers counts number per buckets of 25$ (from zero dollars to 1000$) based on the prediction and the ...
0
votes
0answers
26 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 ...
0
votes
0answers
7 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
votes
1answer
84 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 ...
0
votes
0answers
23 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 ...
0
votes
1answer
28 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 ...
0
votes
0answers
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: ...
0
votes
1answer
69 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 ...
0
votes
0answers
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 ...
0
votes
0answers
8 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 ...
0
votes
1answer
20 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 ...
0
votes
0answers
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 ...
1
vote
1answer
77 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 ...
0
votes
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 ...
2
votes
0answers
27 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 ...
2
votes
0answers
43 views

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 ...
0
votes
1answer
20 views

Is there a way to estimate the distribution from only a small number of outliers?

For example, I was looking at this list of the 93 people who have broken the "10-second-barrier", after reading that sprinter Christophe Lemaitre was the first person of purely European decent to ...
2
votes
1answer
24 views

What kind of functions can have non whole degrees?

Thanks for the help in advance. I am reading a technical report on a regression algorithm that reports a pair of functions as having a total degree of freedom of 5.4. I believe that both of these ...
0
votes
0answers
27 views

A non-negative definate matrix has a non-negative generalized inverse

I'm having trouble proving a N.N.D matrix has a N.N.D G-Inverse. So far I have: If we assume x = Az where x >= 0 and A is a nnd matrix. So if Y is a G-inverse than: x = Az = YAz = Yx >= 0 . Thus ...
1
vote
1answer
29 views

Interpreting output from anova() when using lm() as input [duplicate]

I am learning about building linear regression models by looking over someone elses R code. Here is the example data I am using: ...
0
votes
0answers
19 views

Fitting ARIMAX with lagged X variable (Matlab)

This question is divided into two parts. I currently have a Y vector with 364 data points (Y) and an exogenous variable (X) with 364 data point. X is a good predictor for Y that I want to pair up ...
1
vote
0answers
25 views

What method should I use to analyze data? [on hold]

I failed to pass my regression analysis course as the lecturer didn't say what kind of analysis he wants on the data. The problem was: The index of biotic integrity (IBI) is a measure of the water ...
1
vote
0answers
9 views

Using test data sets in simulation study

I'd like to know the correct way to simulate test data for a simulation study. For simplicity, suppose that I want to test a linear regression model. Chapter 7 of ESL explains that the average test ...
1
vote
1answer
18 views

how can I include a variable ranging from 0 to 1 in a continuous linear model

Imagine that I am trying to estimate house prices with the following model: $Y_p=1 + \beta_{surface} * X_{surface} + \beta_{New York}*X_{New York} + \beta_{Boston}*X_{Boston} $ With $X_{Boston}$ a ...
0
votes
0answers
8 views

glmer predictions: how to extract scores that contributed

I've fit a logistic regression mixed effects model with glmer in R and I'm doing predictions with it. Given a new data that needs a probability prediction, I am interested in extracting the fixed and ...
2
votes
2answers
43 views

Regression analysis if one of dependent variable is almost constant

While doing multi-variate regression, i am encountering cases like below image, where for one of dimension, apart from couple of data points all values are same. Cause of this, model is going haywire. ...
2
votes
2answers
37 views

AIC criterion: definition

I have two questions regarding the AIC criterion : AIC=$2k-2ln(l)$ Where does the number 2 comes from? As we usually minimize it why don't we consider only : $k-ln(l)$. (Maybe I am missing ...
0
votes
1answer
38 views

Compare linear regression models (same and different response variable)

How can I (1) compare two linear models between years and (2) Can I compare 2 models with different response variables? My data have 4 variables: y_meas, x, year, y_calc. "y_meas" is a lab measured ...
0
votes
1answer
22 views

Why does the adjusted r-squared of this model improve with addition of a statistically insignificant variable?

I stumbled on this while doing MLR, and was curious as to why this happens. The adjusted R-squared is (if I understand correctly) supposed to be a way of comparing the predictive quality of models ...
0
votes
1answer
37 views

why is there a huge difference existed in coefficient of determination obtained from 10-fold cross validation?

I'm using gradient boosting regression model (GBRT). To evaluate this model, I use 10-fold cross validation, in each of which I set same param and compute the coefficient of determination as a ...
0
votes
0answers
17 views

ARIMAX model or ARDL?

I would like to study the impact the advertising of a product on its sales (weekly data for 5 years). As the final aim is to forecast what would be the impact on sales of a change in the advertising ...
3
votes
2answers
62 views

Interpretation of multiple logistic regression with interactions in R

I am trying to look at whether 2 variables (one dichotomous categorical and one continuous) predict the occurrence of a dichotomous categorical dependent variable. ...
1
vote
0answers
20 views

Hard Case - prediction of chain stores revenue

Data about average monthly revenue from 2000 stores around whole country. Gini coeff. of reve around 20%, with 50% of observation around average, very thin tails of distribution Explanatory ...
3
votes
2answers
33 views

Regression techniques for capped independent variables

Suppose you are trying to predict height ($y$) based on age ($x$). A straight linear regression won’t work well, since humans stop growing at a certain age. This suggests instead trying to model ...
2
votes
0answers
14 views

mob model tree algorithm

I am trying to figure out the inner workings of the mob function in the party package. I can't figure out how the splitting variable is selected when it is a categorical variable. In the publications ...
0
votes
1answer
25 views

Multiple testing

I am regressing different dependent variables using same set of predictors for all dependent variables such as ...
0
votes
1answer
20 views

Pooling imputed, still not analysed datasets in MICE

I need to do a Multiple Imputation on a dataset with several missing values, and I need to do it with mice, because later I'll have to compare the results with those of imputations ran with other ...
0
votes
1answer
11 views

Multiple regression with dependent variables

I have a dataset with 3 variables (X,Y and Z) and I want to find the best estimates for the constants a,b,c & d. I have been looking into multiregression analysis, but that does not seem to work ...
-1
votes
0answers
16 views

Comparing goodness of fit between lm() and glm()

I may be revealing my relative statistical naivety in asking this, but here goes. Say I have 3 sets of data, to which I fit a characteristic line, be that via ...
1
vote
0answers
69 views

Variance-covariance matrix

$\DeclareMathOperator{\var}{Var}$ How to compute prediction bands for non-linear regression? In the above link, you have mentioned about the variance-covariance matrix of the estimates. What is the ...
0
votes
1answer
36 views

Multiple regression or multivariate regression

Are there any difference in beta coefficients when doing several multiple regression analysis as compared to doing multivariate regression?
1
vote
0answers
21 views

Help with regression and GPA

I'm currently analyzing some data to establish if school performance for particular subjects makes for good predictors of university performance at first year level across all faculties and degrees. ...
0
votes
0answers
8 views

Mapping of input and output values for a Multilayer Perceptron

I try to understand Multilayer Perceptrons for function regression. As a starting reference I am using the matlab neuronal network toolbox. There I mentioned that the tool maps the input and output ...
3
votes
1answer
27 views

Is there a method to disentangle multiple lines of data that are intermingled?

I have 3 temperature sensors that record data once a minute. All 3 temperatures have the tuple value (instant, temperature). The problem is, they may come in a random order and thus there's no way to ...