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

learn more… | top users | synonyms (1)

0
votes
0answers
8 views

How to demonstrate biased estimates of linear regression vs cox proportional hazard survival analysis in R?

I want to perform a really simple simulation of right censored data. Then I want to draw a kaplan meir survival curve and do a cox proportional hazards test. Then I also want to perform a simple ...
0
votes
0answers
11 views

Inconsistent Performance of PCA Results from SPSS

I've completed PCA with my dataset (16 variables) and extracted 3 factors. I then created an Excel spreadsheet where I can enter in user provided data and calculate the scores for each of the three ...
0
votes
0answers
20 views
0
votes
1answer
24 views

Goodness of regression model

What are the main indicators of goodness of a regression model? Are they MSE (mean squared error) http://en.wikipedia.org/wiki/Mean_squared_error , R-squared and adjusted R-squared only? Can mean of ...
2
votes
0answers
13 views

Linear distribution of degrees around a circle

I am trying to fit a model using wind data (0, 359) and time of day (0, 23), but I am concerned that they will poorly fit into a linear regression because they are not themselves linear parameters. I ...
0
votes
0answers
29 views

What is difference between Quantile function and standard normal quantile or probit function?

I'm reading about rank based inverse normal transformation. Basically it's applied to ranked random variable and transform it to normal distribution. I have problem in understanding the transformation ...
0
votes
1answer
17 views

Interpretation of Non-significant Coefficients

My regression uses OLS and annual macroeconomics data. I find one independent variable (x), negative and not statistical significant.From the theory I expected to see (x) to be negative and ...
1
vote
0answers
25 views

Slope of regression model

I am trying to solve the third part of the following question but having some trouble figuring out exactly how I'm supposed to do it: Consider the simple linear regression model of $y$ on $x$, $$y ...
0
votes
1answer
31 views

An example of Instrumental Variables use

In the following example of Greene's Econometric Analysis, he writes at a certain moment: «If the number of weeks worked, and the accepted wage offer are determined jointly, then $ln Wage_{it}$ and ...
0
votes
0answers
22 views

Non-significant interaction effect

I currently have a regression where adding an interaction effect between two significant variables (a float and a boolean) makes them non-significant. Given that this interaction effect is not ...
0
votes
0answers
8 views

Why is path b mediation model insignificant? What does this mean?

Path b (mediator --> outcome variable) is not significant in my mediation model when I ran a regression even though the relationship between the mediator and outcome variable were significant in basic ...
1
vote
1answer
47 views

High correlation between two independent variables, but no multicollinearity?

I have two independent variables which have a Pearson correlation coefficient of 0.98. The two independent variables measure the same underlying construct but only at two different points in time ...
1
vote
1answer
50 views

Is the true linear regressor equal to the average linear regressor?

Let me define my terms. Suppose I have a pair of jointly distributed random variables Y, X, where Y is numeric and X is a random vector. Note that I do not want to assume that Y and X are related in ...
0
votes
1answer
15 views

How is the F-Stat in a regression in R calculated [duplicate]

I am running a regression and I'd like to be able to do the calculation to get to the F stat .3062. How is this .3062 calculated? Can you help? ...
1
vote
0answers
14 views

Rule of thumb for sample size for mixed-effects logistic regression analysis?

Is there a simple way of calculating the minimum number of participants (and/or items) needed for a mixed-effects logistic regression analysis? In particular, what should I do if I don't know what to ...
1
vote
0answers
33 views

giving some predictors higher priority in statistical models

i am working on statistical software debugging. i use various feature selection algorithms in order to discover the bug predictors in programs. for example regression coefficients indicate the ...
0
votes
0answers
23 views

Logistic regression (multinomial)

Having trouble getting my head around this. I should mention, I am not a staistician and all my 'knowledge' is self taught. I am trying to compare 4 hospital sites for patient outcome (either ...
0
votes
0answers
16 views

Results change when variables are scaled [on hold]

I am analysing nested data using LME4 and find that my results (significance) change depending on whether variables are scaled or not!? ...
0
votes
2answers
52 views

How to interpret this interaction in R?

How would you interpret this interaction? The structure of the data is all integer variables. Inc.fix= income, age.fix=age, profit99= profit ...
0
votes
0answers
13 views

how to improve linear regression model [on hold]

i am working on a simple linear regression model for practicing in order to learn machine learning . my model runs correctly however it get a bad score which means it is a bad model so any advice for ...
0
votes
0answers
14 views

Regression with caret and uknown levels [on hold]

I'm trying to perform a cross-validated linear regression with caret. Unfortunately it always fails as some values for levels are not to common and therefore the prediction fails with the error ...
-1
votes
0answers
26 views

Structural Equation Modeling in R throws an error: system is computationally singular [on hold]

I am using Structural Equation Modeling in R. Below is the model that I have specified. The error that I am getting while training the model is: system is computationally singular: reciprocal ...
2
votes
0answers
18 views

incremental quantile regression

I am reading about quantile regression. I wonder if there is a way to incorporate new data into the regression model and update the parameters on the fly. [1] seems to propose a similar idea, however, ...
1
vote
2answers
39 views

Differences between log-log, semi-log and linear regression

Can somebody please explain the differences between using the in the linear/semi-log/log form and also pros and cons of each other.
0
votes
0answers
3 views

Can linear regression slopes be used as covariates in an univariate ANOVA?

Sorry if this has been asked before but I've searched a lot without luck! The closest thing was the following question, which partly answers my question: Can slopes in linear regressions be used as ...
0
votes
1answer
29 views

Adding observations by aggregating existing data

Question I'm aware that generating features from existing data can be a valid method for adding new features for a regression/ML algorithm*, but can you add observations generated from existing data? ...
2
votes
0answers
13 views

Tensor product smooth and Isotropic smooth

In 'mgcv', it is possible to fit two or more dimensional thin plate regression splines but not basis like cubic and P-splines. However, with tensor product smooth (te), we can use all the basis. My ...
0
votes
0answers
17 views

In regression analysis: should all variables be transformed? [duplicate]

I am doing a linear regression analysis between eight variables and as you know normality is one of the conditions for performing regression analysis. Investigating the normality of each variable ...
1
vote
0answers
11 views

Does a factor-by-factor interaction term have any literal interpretation?

Following the explanations in What is the baseline level in a factor-by-factor interaction?, it is my understanding that a factor-by-factor interaction term has no literal interpretation. At the very ...
0
votes
0answers
16 views

How can I calculate the AUC for softmax classifier (e.g., logistic regression)?

At the end of a convolutional neural network(CNN) , there are usually a softmax classifier attached to it. How can I calculate the AUC for the CNN (that is, for the softmax classifier)? Thanks!
0
votes
0answers
24 views

Assumptions and terminology for dynamic regression with endogenous offset ($y_t=y_{t-1}+\beta X_{t-1}+\epsilon_t$)

I'm dealing with a fairly simple time series regression model with the following basic form: $y_t=y_{t-1}+\beta X_{t-1}+\epsilon_t$ I'm assuming that observations of $y$ are known without error. $X$ ...
1
vote
0answers
14 views

Binomial regression does not give coefficients for all IVs [duplicate]

I have a dataset with the dependent variable presence / absence (0 and 1) for a certain species. I have three categorised IV's (2 IV's with 3 categories and 1 with 2 categories). To test the response ...
0
votes
0answers
21 views

Is the constant value ignorable?

I am running a linear regression on SPSS. Basically I have 2 independent and 1 dependent variables; and I would like to understand which of my independent variable is more effective on the dependent ...
0
votes
0answers
16 views

panel data with serially correlated independent and dependent variables

I have a panel data where the independent variables are serially correlated (macro-economic time series), also the dependent variables (company sales growth) are probably serially correlated. Here ...
1
vote
0answers
17 views

How can I plot (multiple) linear regression residual plot “for each coefficient” in R

As a result of linear regression, we can have its residual and see its plot to check whether it shows normal distributed or not as follows : ...
0
votes
0answers
23 views

Reporting a binary logistic regression

The binary logistic regression model was found to be non-significant for my results. What should I include in my results section?for example, would I still report the Nagelkerke Rsquared?
1
vote
0answers
15 views

Why does a robust linear model fitting give a residual standard error?

The way I understood when to use a a robust linear fitting is for example when your variance is not constant (e.g. when you have heteroscedasticity as shown with a Breusch-Pagan test for example) or ...
1
vote
1answer
43 views

Discrepancy between logistic regression and logistic regression results?

Suppose I have a data set of 200 controls (group A; has no memory problems) and 100 cases (group B; has memory problems). And I'm looking at the relationship between memory and cognitive test score ...
0
votes
0answers
13 views

How to find least squares solution with multidimensional data?

I have a data set, on which I want to learn the matrices A and b. So my model is : $$ Y = Ax + b $$ and let's say $x$ is of size $11$x$1$, and $Y$ is $9$x$1$. And I have $50$ observations ($50$ ...
0
votes
1answer
26 views

Choosing weights for regression

I want to weight observations for a regression. I'm worink in R and I'm using the method lmrob from the package ...
0
votes
0answers
8 views

Maximizing mean reversion of residuals

I'm regressing multiple stationary time series in order to maximize the mean reversion of the residuals. I fitted a model via OLS, and discovered that the residuals had a strong negative ...
1
vote
0answers
11 views

Unit weighting for linear composites / regression

Cohen (1990) mentions a regression that I have not heard about before. Here is how I understand his description: Standardize the dependent and the independent variables Regress the standardized ...
0
votes
0answers
10 views

Bonferroni Adjustment in hierarchical regressions

I have some questions about adjusting the alpha level in my analyses. My analyses are as follows: -Gender (block 1), Treatment [yes/no] (block 2), Var1 (block 3) ---> Outcome 1, 2, or 3 -Gender ...
2
votes
1answer
19 views

Approach for estimating expected time required (Regression analysis)

I am analyzing data from a factorial experiment with between subject factor Purifier (two types A and ...
0
votes
0answers
21 views

How do I accommodate for structural change in R? [on hold]

I have time series data for hot dog sales, and I have a quadratic regression that includes monthly seasonal dummy variables. ...
0
votes
0answers
27 views

Stata - regression homework question [on hold]

I'm currently attending an econometrics class at my university and it's not my strongest side. So we got a homework problem set and I am having trouble solve it. Here it is: ln E[Y | X1, X2, X3] = ...
0
votes
0answers
6 views

Parameterization of the ANOVA model and interpretation of the overall F-test

I've recently encountered the following concept regarding linear regression: the inclusion of an intercept will change the interpretation of both the overall F-test and the individual parameter ...
6
votes
1answer
110 views

Why to report R squared?

If adjusted R squared is superior to R squared, then why do statistical software continue to report the latter? Is there any kind of situation when a researcher may prefer to use R squared instead of ...
0
votes
0answers
18 views

Can I take mean of correlation coeficients for equally spaced data sets?

Historic market (Cash) prices and future contract prices are available for last 4 years. I have found correlation between Jan'11 market price with Jan'11,Feb'11 and March'11 future contract prices ...