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

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Number of parameters for AIC for a particular model

I know there have been a few well answered questions on this topic, but i have found myself in a bit of a special case this time. I am using AIC for model selection, and i am having trouble counting ...
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4 views

Hodrick prescott derivation in layman term. Could explain what is telling the first and second term in the equation

I am currently working on the hodrick Prescott filter. I would like to understand the equation in layman term so that I could understand myself the concept as a non mathematical person.
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7 views

How to down weight correlations in my microarray analysis?

Background: I have been tasked in one part of my analysis to reproduce a method used in another study as follows in bullet points form: Microarray data from a number of time points Calculate ...
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0answers
12 views

Linear post-treatment of nonlinear regression

I have often found in practice, using nonlinear regression techniques such as feedforward neural nets or random forests, that the resulting actual-vs-fitted plot (on training set) seems sub-optimal, ...
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1answer
44 views

Comparing residuals between OLS and non-OLS regressions

Suppose you want to estimate a linear model: ($n$ observations of the response, and $p+1$ predictors) $$\mathbb{E}(y_i) = \beta_0 + \sum_{j=1}^p \beta_j x_{ij}$$ One way to do this is through the OLS ...
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10 views

Problems with calculation of numerical identification w.r.t. ANOVA smooth for large scale matrices

Suppose we have two (centered) Spline-matrices $\boldsymbol{B_1}$, $\boldsymbol{B_1}$. Then $\boldsymbol{X_1} = [\boldsymbol{B_1},\boldsymbol{B_2}]$ contrains lower order smooths and ...
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2answers
50 views

How does the inclusion of an intercept change the variability of the residual?

I want to use the variability of the residual as a measure M and then test whether M is higher or lower after some event. However, I estimate separate regression before and after the event to obtain ...
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7 views

Autoregressive model with input variables in proc arima procedure

I am currently working on the time series analysis for series Y but I have to use other two variable A and B as an input variable in SAS proc arima procedure. But I am unable to interpret the cross ...
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17 views

Use of factor analysis + regression

Independent Variable: I have a survey of 50 states indicating the amount of control the state board of education has in 31 areas answered on a three point scale (1 = total control; 2 = partial ...
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1answer
34 views

What are 'aliased coefficients'?

While building a regression model in R (lm), I am frequently getting this message ...
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2answers
40 views

How does random Forest work for regression?

I am an absolute beginner in field of machine learning, I started doing titanic assignment in Kaggle and found(read some where) Random Forest is the best fit. I started reading about random forest and ...
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22 views

Logistic vs. Linear regression for recovery rate modeling

i am trying to model recovery rates in my data that are in the range of (-.1,+1). Around 8% of my observations are negative too. Broadly, below is the dist.: RR<0: 8% RR=0: 30% RR>0 and ...
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11 views

Measures of goodness-of-fit using multiply imputed data in Zelig

I am running a logistic regression model in R using multiply imputed data created using Amelia II, which I am then analyzing using Zelig. I would like to be able to report some measures of ...
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23 views

How to propely transform log based linear regression model for a prediction

I built a model in the following structure (r): model<-lm(log(target+1) ~ var1+log(var2+1), data=dat) how can I transform the results (coeffecients) so I'll ...
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1answer
12 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
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15 views

How to perform multilevel interaction

I have 400 observations = 100 individual * 4 years. Which equation is correct? $$x_{1} + x_{2} + \left(x_{1}x_{2}2013\right)+ \varepsilon$$ $$x_{1} + x_{2} + \left(x_{1}2013\right) + ...
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1answer
15 views

R regression with categorical response variable

I have four variables, two are categorical and two are numeric: ...
2
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1answer
29 views

SEM variances of residuals fixed to 1?

I'm trying to perform structural equations with two second-order latent variables and five first order latent variables (since "a picture is worth a thousand words" I pasted my model below). To ...
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0answers
15 views

How to pick the “sigma” when sigma clipping?

In astronomy (and I'm sure in other places as well) it is very common to use sigma-clipping as the outlier rejection scheme. The idea is that you regress the data, subtract the fit from the points, ...
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1answer
47 views

Linear model- Understanding performances on training and test sets

I have a small normalized data set, 30 observations and 18 Predictors. All are continuous and some variable are related. I ran linear regression on it using Weka. The model automatically dropped some ...
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14 views

ANOVA to test overall significance of model in linear regression with only continuous predictors

A normal ANOVA model always needs a categorical variable as a predictor(the factor/group) right? Please let me know the reason if you think otherwise. So in case of a linear regression with only ...
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18 views

Is there a way to customize my likelihood function for logit models using speedglm/biglm/glm packages?

My goal is to fit a custom logistic regression/survival analysis function using the optim/maxBFGS functions in R and literally ...
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0answers
18 views

why are rlm and rreg functions in S-Plus giving different results?

I used the S-PLUS functions rreg and rlm to perfom robust regression and I obtained different results. Is this expected?
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1answer
37 views

Can I compare two regression coefficients

I am comparing treatment outcome to two therapeutic treatments. Specifically, I am looking at how attachment moderates the relationship between therapeutic alliance and outcome. I hypothesize that the ...
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1answer
49 views

What is the estimation techniques used in lm() in R?

I'm wondering what is the estimation techniques used in lm(). If it's OLS, how could we perform a log likelihood test by logLik()? What's the difference between lm() and ols(), mle() and other ...
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14 views

polynomial regression model

Please, could you help me in answer on my question which it is as follows: I have 7 factors with 3 levels and no. of experiments are 27 tests, Can I build polynomial regression model with these data ...
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52 views

small sample size, large number of variables (most categorical) - how to proceed?

I would be grateful for general guidance/advice about data analysis with some data that is problematic for me because of the small sample size, and the large number of categorical data. I realize this ...
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11 views

How to test difference between weighted and non-weighted slope in R?

I have a dataframe with the following column: Year, Temperature, Num.Species which are all numeric variables. Each row represent the number of species observed a certain year and the mean temperature ...
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11 views

some suggestions for analyzing two-factor within subject design?

I'm doing a two-factor within-subject design experiment, and the two factors are all categorical variables. factor one has four categories, while factor two has two categories, and is counterbalanced. ...
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1answer
78 views

Weighted regression

I have a response variable, y.hat, that is an estimate of animal abundance. I know the standard error of y.hat. I'm skeptical ...
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1answer
49 views

What's the typical range of possible values for the shrinkage parameter in penalized regression?

In lasso or ridge regression, one has to specify a shrinkage parameter, often called by $\lambda$ or $\alpha$. This value is often chosen via cross validation by checking a bunch of different values ...
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9 views

Error messages when doing regression in SPSS

I need to do a number of regressions in SPSS but keep getting error messages. For example - "There are X cells (i.e., dependent variable levels by combinations of predictor variable values) with ...
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16 views

Regression equation formatting

I have a simple question for you, which has to do with style. Since I am a novice in writing research papers, I have the small issue of not knowing how to represent an equation in an acceptable way. ...
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1answer
43 views

Help with MLE regression

I have a data set containing two variables x and y. I want to estimate the parameters for a regression model. The regression ...
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1answer
94 views

Rule of thumb to rule out reverse causality in the OLS model

Let' say I have a regression model: $y=a+b*x+error$ Suppose $x$ is income and $y$ is consumption. The hypothesis is that higher income leads to higher consumption and hence, the coefficient on $x$ ...
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8 views

Count variable as control variable in regression in SPSS

I'm doing a research on development of audit fees in 2005-2012. I'd like to see if there's a downward or upward trend in them. I have made a count variable of the years (2005=1 2012=8) and now should ...
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0answers
16 views

General Linear Model (GLM) with Continuous Variable and Categorical Variable (SPSS)

I would like to perform a GLM with a continuous variable and categorical variable as fixed factors. For e.g. Weight predicted by Height and Gender. From what it seems, the univariate GLM option in ...
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19 views

Probabilistic interpretation of regression for justifying squared loss function

I was reading Andrew Ng's CS229 lecture notes (page 12) about justifying squared loss risk as a means of estimating regressions parameters. Andres explains that we first need to assume that the ...
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2answers
20 views

AR terms and independent variable as regressors

After trying several models with my data, R^2 and p values are showing my model looks like below. ACF plot tells me AR term is significant. Insights into data tells me change in 'x' would have ...
2
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1answer
33 views

What are the relative merits of testing significance of a regression coefficient

If I have several hundred coefficients generated by running multiple variable regression model (keeping it as broad as possible by not specifying the nature of the predictors and outcome variable), it ...
2
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0answers
22 views

Maximum Rank Correlation for panel data

Let $Z=(Y, X)$ be an observation from a distribution $P$ where $Y$ is a response variable and $X$ is a vector of regressors. Assuming the following model: $Y = F(X'\beta, u)$ where $X'\beta$ is a ...
2
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2answers
49 views

Which property of count data make mean-variance dependency?

I have read about the fact that, there is dependency of variance on mean of count data.In most of cases they do variance stabilization transfomration as preprocessing step of data modeling. I wonder, ...
3
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2answers
39 views

Non-linear least absolute deviation regression with multiple global minima

I am fitting a single exponential decay formula with three parameters (a,b,c): y ~ $a \exp(-xb) + c$ using the LAD cost function: $ \min \sum |(y - f(x))| $. $x$ is in units of time (as is $b$), and ...
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10 views

Interaction between percentage and population size in a regression

Assume I have a regression type model. Are their any statistical and/or substantial reasons NOT to include a two-way interaction which consist of a percentage and the corresponding population size. ...
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0answers
24 views

Getting unexpected lme results

I am evaluating an experiment in which subjects had to rate quality of audio files. The design of the experiment is repeated-measures. So I'm trying to figure out which factors have an impact on ...
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0answers
11 views

regression. sufficient dimension reduction [duplicate]

in sufficient dimension reduction technique, we image predictors on central subspace. this procedure product new predictors for us that are linear combination of original predictors. in addition, new ...
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1answer
47 views

PCA vs SVD - understanding difference and preference of SVD over PCA [duplicate]

I understand that PCA and SVD are similar - PCA removes the mean and SVD doesn't? I think I have an understanding of PCA - you would use it to reduce dimensions of data and separate it out into ...
0
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1answer
34 views

Hypothesis Testing using dichotomous and 7-point Likert scale

I am working on testing the following hypothesis: H1: People who are worried about their health will consume yogurt H0: People who are worried about their health will not consume yogurt I have ...
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0answers
8 views

hierarchical logistic regression Block non-significant, interaction significant

I'm using hierarchical logistic regression and having some difficulty. Im trying to predict self-harm vs none based on IVs age, gender, alcohol, educational attainment. They are all yes/no except ...
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56 views

Restriction matrix for a VAR

In New Introduction to Multiple Time Series Analysis by Luetkepohl (2005), section 5.2.1, it says that one can specify linear restraints for a VAR, $Y = \beta X + U$, in the form $$ ...