Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
0
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0answers
49 views
How to handle negative Y values with exponential regression?
I have data points that include one instance of a negative y value. With this data, is it possible to generate a exponential decay function in a way that is mathematically sound? The only variable is ...
0
votes
2answers
100 views
Specific estimates about fuel consumption - Simple linear regression?
I am working on a story problem for a project.
"You work for a small environmental foundation that wants to analyze fuel consumption. Your boss (in the year 2002) has asked you to help her analyze ...
0
votes
1answer
20 views
Matrix image regression or regression of subscales
A person is given 10 sample images (based on the same image) with corresponding techniques on how the image was achieved. I want to regress the matrix bitmap of the image of the 10 images on the image ...
0
votes
0answers
27 views
ols regression on stationary series
I am trying to regress (OLS) some time series on stock returns. I am not interested in regressing the returns of those time series on my stock returns, but I want to include information about the ...
0
votes
3answers
76 views
Regression for a Rate variable in R
was tasked with developing a regression model looking at student enrollment in different programs. This is a very nice, clean data set where the enrollment counts follow a Poisson distribution well. I ...
3
votes
6answers
93 views
Time spent in an activity as an independent variable
I want to include time spent doing something (weeks breastfeeding, for example) as an independent variable in a linear model. However, some observations do not engage in the behavior at all. Coding ...
3
votes
2answers
136 views
What are good RMSE values?
Suppose I have some dataset. I perform some regression on it. I have a separate test dataset. I test the regression on this set. Find the RMSE on the test data. How should I conclude that my learning ...
1
vote
1answer
42 views
Standard Error of Standard Deviations Estimated with gls in R
In the gls fit shown below, the estimates of the standard deviation for each level of X are apparently given by the product of (1.000000, 3.913972, 10.684698, 11.350910, 26.476561, 27.255072) times ...
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3answers
108 views
How to report SPSS OLS output?
Consider the model below:
In many research papers, significance of statistical results are indicated by *, **, and ...
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0answers
20 views
Output of logistic regression model [duplicate]
I have built a logistic regression model using SPSS to predict a variable (0 or 1)
The coefficients are as below: -0.005, 0.132, 1.349, -1.321,-0.265,-0.981, intercept = -1.522 when I sub in the ...
3
votes
1answer
68 views
Statistic For The Curvature or Non-Linearity Of Data Set
I'm trying to estimate the curvature/structural complexity of datasets, or the amount by which it is non-linear. The datasets are mostly very linear but with instances of very arbitrarily structured ...
1
vote
1answer
25 views
Calculating trend for 3 dimensional data
Forgive me for a potential dupe, as I don't know the correct terminology for searching for an existing question. Also please add tag "trends" or similar, as I don't have the reputation to create new ...
1
vote
0answers
48 views
Interpretation of Translog regression
I'm a beginner in R and Im wondering how to interprete my results.....
My question is about the results that I got after I did a regression on the Translog production function for panel data:
$ ...
0
votes
1answer
64 views
Modelling two correlated variables
I wish to simultaneously predict two correlated time series. Here is a plot of one time series against the other:
At the moment I have separate linear regressions for both of them which rely on ...
0
votes
0answers
40 views
Does case control ratio matter in Cox regression?
I am trying a Cox regression model to do survival analysis/hazard ratio of developing diabetes. But my case control ratio is like 9:1 (i.e. 900 cases and and 100 controls). Will this big difference in ...
0
votes
0answers
26 views
Question about the relevance of random effects in the big panel-data context
In general, or at least as I know, the "estimation" of random effects does control for the individual/group/... specific variation.
Hence by controlling for this variation by a random intercept- or ...
0
votes
0answers
34 views
Problem with lqmm. Very long time to run and issues with error handling
I am trying to use lqmm to fit some models and it appears to be working ok with my data (N 2000 w/ clusters=1200). I am using a call like this:
...
0
votes
0answers
25 views
Compare the predictive power of a model between datasets
I have two sets of continuous response data for the same group of species, but in different areas (area a and area b). I am building a model for each area separately, to predict the area-specific ...
5
votes
3answers
147 views
Explanation of minimum observations for multiple regression
I feel like every question I've asked on CrossValidated has lead back to looking at the number of observations I have per variable. I understand that there are many rules of thumb out there depending ...
0
votes
0answers
35 views
Binomial logistic regression in Java
does anyone have any idea of a Java library that performs binomial logistic regression? i've looked at the Kazanova, Weka libraries but does anyone know of any other?
thanks
2
votes
1answer
68 views
Power of a Multiple Linear Regression
I have a set of models that are the result of a multiple linear regression. I would like to calculate the power for each of these models. I found this tutorial on calculating the power using G*Power. ...
3
votes
2answers
77 views
Noisy linear relationship: Can the functional form be known?
Let's say I know the relation between x and y is linear yet noisy. Given a noisy (x,y) ...
2
votes
1answer
58 views
Principal component analysis (PCA) on long-tailed data
(1) When doing PCA, do you assume the variables to be bell-shaped? Say if I have a bunch of variables, some are bell-shaped but some have characteristic long (right) tails (highly skewed and ...
5
votes
1answer
182 views
Wald test in regression (OLS and GLMs): t- vs. z-distribution
I understand that the Wald test for regression coefficients is based on the following property that holds asymptotically (e.g. Wasserman (2006): "All of Statistics", pages 153, 214-215):
$$
...
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0answers
61 views
How big of a dataset can R or SAS handle for regression?
On a standard computer (~3-6gb RAM) with 2 - 4 processors.
What are the size restrictions on a matrix of data for R or SAS?
2
votes
1answer
42 views
What impact does including more predictors have on the CI for R squared?
More precisely I mean "All other things being equal, what impact does including more predictors ('IVs') have on the CI for R squared?"
Say we'll get an R squared of .30 no matter whether we include 4 ...
0
votes
0answers
29 views
Convergence of batch gradient descent in logistic regression
I am not really sure about how it behaves when using batch gradient descent in logistic regression.
As we do each iteration, $L(W)$ is getting bigger and bigger, it will jump across the largest point ...
1
vote
1answer
37 views
Regression Estimation difficulties
My regression problem is properly formulated, but is encountering serious computational difficulties.
Dependent: $Y$ = multinomial
Independent: $X_1, \dots, X_{90}$ = linearly independent set of ...
1
vote
1answer
57 views
How to interpret a non significant independent variable?
I conducted a regression analysis using R's lm() function. One of the independent variables shows no significance (p = 0.89), which contradicts the hypothesis that is should have a significantly ...
0
votes
1answer
72 views
Variable Selection in R: Choosing One Variable from Each of 3 Buckets of Variables
I have a regression model that looks like the following
glm.nb(formula = y ~ Gender + Age + x1 + x2 + x3, data = df)
In my problem, there are 20 possible choices ...
0
votes
0answers
26 views
Two IVs (schools) and 3 IVs (grade levels in each) where there are 2 DVs (math and reading scores)
Is MANOVA the correct test? I am looking at 3 grade levels in each of the two middle schools. I want to compare the standardized scores (reading and math) of students in each grade level to the same ...
3
votes
2answers
104 views
Logistic regression: categorical predictor vs. quantitative predictor
Why is it the case that when I run logistic regression with one categorical predictor, my regression is not significant whereas if I run the logistic regression with the same variable except it is ...
-1
votes
1answer
39 views
What's the convergence rate when solving L1 regularized optimization via coordinate descent with tiny step? [closed]
Wondering if there is an established result for the convergence rate when solving L1 regularized optimization via coordinate descent with tiny step? By "tiny step" I mean the step is always set to a ...
3
votes
1answer
94 views
Why don't we look at $R^2$ when fitting an autoregressive model?
$R^2$ measures explained variance. In an autoregressive model like AR(k), we are carrying out a linear regression, and as such we would have an $R^2$ and an ...
1
vote
0answers
60 views
Is LOESS the appropriate way of visualizing my RT data?
I am conducting a Lexical Decision Task where my dependent random variable is Response Time (RT).
My experimental design consists of 5 blocks of a 100 trials each. In each block, 50% of trials ...
2
votes
1answer
162 views
Moderation in repeated-measures design?
Context: Both dependent $(Y_1,~Y_2,~Y_3)$ and independent $(X_1,~X_2,~X_3)$ variables were measured repeatedly at three time points, $\text{Time}_1$, $\text{Time}_2$, and $\text{Time}_3$. Moderator ...
0
votes
0answers
41 views
Repeated measures data
Suppose you have data where you measure a subject at 10 different time points but some subjects are measured at less than 10 time points. Can you still apply standard methods to model observations at ...
0
votes
1answer
119 views
R2 of validation sample
After removing 25% (21 observations) of the sample as a holdout, model selection on the original 75% of the a sample led to a six variable multiple linear regression with R2 of 54%.
A simple ...
3
votes
1answer
51 views
Estimating age based on height
I wonder if it's possible to estimate a child's age given the child's measured height.
I have found this height chart:
http://resource.nhi.no/resource/4281-21-hoyde-gutter-5-19-who.pdf
Is it ...
1
vote
1answer
45 views
Back transformation of an MLR model
I've obtained a multiple linear regression model in the form
$$
\mathrm{log}(Y) = \beta_0 + \beta_1x_1 + \dots + \beta_4x_4 + \beta_5x_1x_2 + \dots + \beta_{10}x_3x_4 + \beta_{11}x_1^2 + \dots + ...
3
votes
1answer
122 views
Significant difference from regression confidence intervals
I have a question about statistical significance in relation to confidence intervals from linear regression. I'm obviously far from a stats expert, and I've been searching for the answer to this, ...
0
votes
1answer
22 views
Using a normal distirbution for count data
I was just wondering if it is possible to use a normal mixed model for count data. Would it be better to use a Poisson regression if your response is count data?
1
vote
2answers
78 views
Explain overfitting / data leakage to a colleague
I have a situation where we are calculating a customer life time value using some binary variables (ie have they purchased xyz widget?, etc.) and multiplying by a number that we believe approximates ...
1
vote
2answers
97 views
T-test / ANOVA on Box-Cox transformed non-normal data
Suppose I apply a Box-Cox transformation to my data and now it looks rather like a normal distribution. I then add another dataset, transform it by Box-Cox with the same lambda and run a t-test to ...
0
votes
1answer
48 views
Log, geometric and elasticity
Suppose I want to calculate the average annual growth in GDP per capita from year 1980 to 1988. I suppose this is done by ln(gdp per capita 1998) - ln(gdp per capita 1990) ? So for example:
...
-7
votes
2answers
154 views
Can you see any S-curve in the scatter plot [closed]
two variables >>> scatter plot >>> relationship >>> ? S-curve!
1) any S-curve?
2) S-curve?
3) if S-curve no scatter plotting?
4) linear correlation=0.85 >>> meaningless?
5) explain the relationship
...
0
votes
0answers
64 views
Regression with a ordinal scale dependent variable in the context of panel data
In my panel data I observe a quite large amount of different individuals for a fixed time duration. The time axis is fixed for every individual, i.e., I observe 20 time points for every individual.
...
5
votes
1answer
65 views
Constant variance assumption in regression model
My question is how do we check the constant variance assumption in a regression model?
1
vote
0answers
51 views
Forward Stepwise selection
I am assuming the following model:
$Y = \beta X + \epsilon$
Here both $X$ and $Y$ are matrices. I fit the least squares model without any regularization and get the matrix $\beta$. I would like to ...
4
votes
2answers
121 views
What is better to transform doing linear regression, response or explanatory variable(s)?
Maybe it is a very basic question and already answered, but I could not find a clear answer.
My plots of response vs. predictors show "curved" relationship, and log-transformation can help to achieve ...
