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

learn more… | top users | synonyms (1)

1
vote
1answer
15 views

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 ...
0
votes
2answers
20 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 ...
3
votes
2answers
50 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 ...
0
votes
0answers
12 views

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 ...
1
vote
0answers
14 views

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 ...
1
vote
1answer
28 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 ...
0
votes
0answers
17 views

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

My question is about logistic regression, and I want you to advice me to use the appropriate method for my problem: here is the description : My goal is to determine the risk factors for a disease ...
1
vote
0answers
18 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 ...
0
votes
0answers
26 views

Inflation as an independent variable

Assume a model like this, basically explaining stock market returns with a bunch of stuff: ...
1
vote
1answer
25 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 ...
0
votes
0answers
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?
1
vote
0answers
23 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 ...
2
votes
0answers
17 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 ...
1
vote
0answers
18 views

Comparing nested, non-linear models

I would like to compare the fit of two non-linear regression models: 1) $$ Y = (\Pi^{10}_{i=1}\beta_i^{x_i})^{1/\Sigma \beta} $$ 2) $$ Y = \begin{cases} (\Pi^{10}_{i=1}\alpha_i ...
1
vote
1answer
44 views

Regresssion of Accurate Data

I'm collecting calibration data for a device which involves three variables $S$, $L$, and $x$. For a given coordinate $(S, L)$, the device will provide me with the corresponding value of $x$ to a high ...
4
votes
0answers
24 views

R packages that work with biased samples

I'm working with a biased sample of web users. I'm only able to track responses of users who have navigated my site in a certain way, and I'd like to run an analysis to determine how certain factors ...
0
votes
0answers
34 views

How does this algebraic relationship among expectations work?

Find the expected mean squares error of lack of fit. Trial: $$SSLOF=\sum_{1}^mn_i(\bar y_i-\hat y_i)^2\\=\sum_{1}^mn_i(\bar y_i-\bar y)^2-\sum_{1}^mn_i \hat\beta_i^2(x_i-\bar x)^2$$ and ...
2
votes
0answers
11 views

Evaluate deviation from negative binomial model

I'm trying to figure out how to determine to what extent a sample deviates from a negative binomial model fitted to a larger population. As an example, I generated counts of doctor visits for a ...
1
vote
1answer
34 views

AR(1) on autocorrelated data that is not a time-series

I need to apply a regression model on observations that is not time series data but each observation presents a store and the amount of cartons that gets sent to that store. For instance ...
0
votes
1answer
13 views

On using an orthogonal series to estimate a regression function

Suppose I have a function $g\in L_2(\mathbb{R})$, and we observe variables two -vectors $(Y_i,X_i)$ such that $Y_i = g(X_i) + U_i$ for some IID error terms $U_i$. If I want to estimate $g$, I want to ...
0
votes
0answers
14 views

Compare the marginal effect for a dummy variable with a continuous variable from a probit model

I use probit model for one regression which consists one independent dummy variable that captures whether the firm is unionized or not. I also estimate the same probit model instead of consisting ...
0
votes
0answers
32 views

Fixed / Random Effects Model

I have the following kind of panel data set, without a time variable. 20 countries are the panel variable and provide data on 48 other countries. The independent variables are 6 (intercorrelated) ...
0
votes
1answer
15 views

clustering of singular values

let us consider following graph of singular values i want to make some kind of clustering of these data,namely to seperate main components from non main components,let say signal components ...
7
votes
1answer
268 views

What is the difference between multiple regression & mutivariate regression?

I have data on GDP growth as a dependent variable and growth in main production sectors of Pakistan such as mining, electricity, communication, manufacturing and electricity. I am supposed to run a ...
0
votes
1answer
8 views

Difference between ep-SVR and nu-SVR (and least squares SVR)

I am trying to find out which SVR is suited for what kind of data. I found out 4 types of SVRs: epsilon, nu, least squares and linear. I understand linear SVR is more or less like lasso with L1 Reg. ...
0
votes
1answer
40 views

Offset variable in Poisson regression makes model worse

I'm using a Poisson regression to model count data (number of orders). My observation lengths are different, so I tried to include an offset variable in the model. The problem is that when I estimate ...
0
votes
0answers
28 views

How to interpret Weka logistic regression output for a nominal attribute and its coefficients? [on hold]

Kindly help me interpreting the output of logistic regression in Weka. I have a data set. Below is the arff file. There is one numeric attribute and 3 nominal ...
3
votes
1answer
91 views

Do Beta weights from regression have error terms?

I am looking at standardized regression weights (i.e., Beta weights). I was thinking of reporting the errors next to the weights in a figure, but upon some thought I was debating whether such errors ...
2
votes
1answer
61 views

How to compare whether the coefficients of two independent variables statistically different from each other?

If I have two independent variables and they are dummy variable along with other independent variables and I run a linear probability model, I want to compare whether the coefficients of two dummy ...
0
votes
0answers
10 views

Construct matrix of stacked variables in VAR regression

I am trying to NOT use packages for the estimation of models in order to have a deeper understanding of how things work. Currently, I am trying to estimate a VAR(1) (vector autoregression of first ...
0
votes
0answers
22 views

Help interpreting R linear model fit [duplicate]

I have observed variables power$values. I am trying to model this process using a second set of observations, such that $P = M\cdot X + B$. $P$ is the function ...
1
vote
1answer
32 views

What preponderance of a single outcome renders binary logistic regression ineffective?

This question was motivated, but is separate from, the question I posted here: How can I improve the predictive power of this logistic regression model?. In that case the 'cancer' outcome was ...
1
vote
3answers
242 views

How can I improve the predictive power of this logistic regression model?

I am using SPSS to analyze a data set which aims to predict whether individuals have cancer based on five symptoms (a, b, c, d, e). In this data set most individuals have cancer. I ran a Binary ...
1
vote
2answers
33 views

what does the correlation of Random forest regression tool in R represent

I've built a random forest model (regression model) using randomForest package in R, and I calculate the correlation between the predicted values and the actual ones in order to know how the trained ...
2
votes
1answer
24 views

Is it ok to spit non-normal variables in tertiles and put them into multivariate regression models?

I am now reviewing a paper in which the authors decided to predict a DV through linear regression using, beyond other variables, dummy variables obtained from a tertile split of continuous variables, ...
2
votes
1answer
32 views

SPSS linear regression - variables that are percentages

I have some data about music styles played at festivals. It looks like this: Based on this (and other) data, I'd like to make a model to explain the price of a ticket for each festival. However I'm ...
0
votes
0answers
29 views

How to do Regression Discontinuity Design in R [on hold]

I am having trouble with doing regression discontinuity design in R. Could anyone show me a syntax for R to do RDD? The exercise I have is y= wealth x=winning margin covarites= education, past ...
2
votes
1answer
27 views

Cardinal data as dependent variables

I wanted to find out if there are any implications to using OLS when i have cardinal data as dependent variables. So my dependent variables are counts of a certain outcome and they exist as natural ...
0
votes
1answer
36 views

How to make stochastic gradient descent algorithm converge to the optimum?

(Background info taken from my blog) In logistic regression, the hypothesis function, which models the relationshiop between the dependent variable $P(y = 1)$ and the independent variable $X$, is : ...
0
votes
0answers
36 views

Explanatory power of variables in multiple regression

Suppose that I have a regression model with two explanatory variables: $Y = b_0 + b_1X_1 + b_2X_2 + \epsilon$ The determination coefficient $R^2$ measures the amount of variability in the response ...
0
votes
0answers
19 views

Feature scaling for classification and regression

Is it true that one should generally scale each of the features before feeding them into common classification models such as Support Vector Machine, Logistic Regression, etc? What about for ...
0
votes
0answers
22 views

Problem with year as a factor GLMM

So I need to do a GLMM, I do it this way, with package lme4 glmer(y~x1+x2+x3+year+(1|x4),family=binomial In my data, year is a factor (4 levels). So when I run my glmer, I have my result like this x1 ...
1
vote
0answers
20 views

Are these descriptions of batch gradient descent algorithm conflicting each other?

The first one is from Andrew Ng The second one is from Francis Bach I might be a little confused, but why is there a summation of partial derivatives in the second description and none in the ...
1
vote
0answers
20 views

Standardizing count variables in panel data with overdispersion - R or Stata

I'm running a regression where the dependent (response) variable is a highly dispersed (slightly zero-inflated) count and the explanatory (independent or predictor) variables are continuous, counts as ...
0
votes
0answers
22 views

What is multi run lasso regression?

I have problem in understanding of multi-run lasso regression. Basically, I know what is lasso regression, but don't know what is multi-run lasso regression, which sometimes I see literatures. Does ...
0
votes
0answers
28 views

What is PRINCIPAL HESSAIN Direction Model, how and where can I use it?

I'm a M.Tech student going through my academic project-work, here I have asked to develop a optimal design and a best equation to fit the data for a Leaching, Solvent extraction and Electrowinning ...
0
votes
4answers
61 views

confidence intervals for values estimated from the nonlinear regression model

I have a question about nonlinear regression and confidence intervals for values estimated from the model. Here is my problem. I have sets of data where $X$ is the logarithm of the dose of a chemical ...
1
vote
0answers
30 views

Fit a GARCH (1,1) - model with covariates in R

I have some experiences with time series modelling, in the form of simple ARIMA models and so on. Now I have some data that exhibits volatility clustering, and I would like to try to start with ...
1
vote
0answers
18 views

Parameter tuning in lars (lasso) matlab

I am trying to use lars (matlab implementation:http://www.ece.ubc.ca/~xiaohuic/code/LARS/LARS.htm). I want to do a leave one out cross validation on my data using this code. I have the following ...
0
votes
1answer
38 views

Multiple linear regression through orthogonal matrices

An example of linear regression could look like: $min \sum_{i=0}^{m}||x_i A - y_i||_2^{2}$, where ${x_i, y_i} \in \mathbb{R}^n$ and $A \in \mathbb{R}^{n\times n}$. I am interested in knowing how do ...