Refers to any model where the a random variable is related to one or more random variables by a function that is linear in a finite number of parameters.

learn more… | top users | synonyms

0
votes
0answers
13 views

Random intercepts as response variables: Is there a name for this method?

I'm trying to find the name of this method (and ultimately a reference). The approach is as follows: 1) Fit a mixed-effect model with a random intercept 2) Use the estimated random intercepts as ...
0
votes
0answers
27 views

How to calculate p value from ANOVA function for LMM results?

I have used ANOVA function so that I can get the overall p value of significant factors: ...
0
votes
0answers
24 views

To get the overall significant p value, am I on the right track for LMM?

According to this document: http://www.bodowinter.com/tutorial/bw_LME_tutorial2.pdf I can get the overall p-value of fix effects by comparing models that I would like to know to null model. In my ...
0
votes
0answers
11 views

Temporal trends with missing values

I need to calculate the temporal trends for some climate variables with missing values. For example, last frost days defines as the last day of year with minimum temperature less than 0C. However, ...
0
votes
0answers
16 views

Can I combine two pairwise comparisons?

I am using LMM in lmer. To find the most optimal model, I compare models of three-level with two level using ANOVA function. If it turns out that no significant difference between these two, then I ...
3
votes
1answer
53 views

Design of matrix of contrasts in R

I am doing some post-hoc comparisons (in lme4, but here I'll just present a simple linear model), and I am having a hard time making sure that I am building the right matrix of contrasts to test ...
0
votes
0answers
24 views

Hidden Markov Models relationship

I have a question regarding a small investigation that I have been conducting into the relationship between the length of observation sequence, T, on which two decoders (BCJR and classic Viterbi) ...
0
votes
0answers
6 views

example of a non-trivial data where leverages would all be equal

i was asked to describe a non-trivial data (n not equal to =/1) example where the leverages would all be equal for QR decomposition question. could someone help?
2
votes
1answer
48 views

Consistency of OLS in presence of deterministic trend

For consistency of OLS estimator for linear model $$ y_i = \beta^T x_i + \epsilon_i, \; i = 1,\cdots, n, $$ the model assumptions are usually (the ones I am familiar with) The sequence of random ...
0
votes
1answer
58 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 ...
3
votes
1answer
107 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 $x$ ...
2
votes
2answers
22 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
votes
0answers
80 views

Mixed effect linear regression model output interpretation

just fitted mixed effects model: Linear mixed model fit by maximum likelihood ['lmerMod'] Formula: price ~ variable + (1 | product) Data: podzbior ...
0
votes
1answer
37 views

Differenence between hierarchical linear regression and moderated multiple regression

What is the difference between hierarchical linear regression and moderated multiple regression? If I have one and two moderator variables and my models are: model 1- IV model 2- adding two ModVs ...
5
votes
0answers
78 views

Confidence bands for QQ line

This question doesn't specifically pertain to R, but I chose to use R to illustrate it. Consider the code for producing ...
6
votes
3answers
354 views

What does “curvilinear” mean?

As far as I can tell, curvilinear is defined vaguely but means the same as nonlinear. Is that correct? Or does curvilinear have a distinct definition?
1
vote
2answers
57 views

Do you need to change instances to rates for OLS regressions

I am interested in performing a regression on data on a population. This population causes events X and Y. I have monthly data for population, event X, and event Y. Do I need to change my variables X ...
0
votes
0answers
23 views

How to calculate prediction intervals from a multiple linear regression with simulated future Xs

I am using a multiple linear regression model to generate 80% prediction intervals based on simulations of future X values. While I understand how to calculate prediction intervals typically (such as ...
0
votes
0answers
13 views

Can variance in error term be estimated without fitting a line?

In this exercise, I was asked to prove that the simple linear regression - ( $Y_i=\beta_0+\beta_1X_i+\epsilon_i$ with all the usual basic conditions) - of $\{Y_{ji}\}$ for each $X_i$ is the same as ...
0
votes
0answers
29 views

How can I use the sufficient statistics (variances, covariances, means) to estimate a linear regression model in R?

My question is simple: is there a function in R which estimates the linear regresion model in a similar fashion as lm, but only ...
1
vote
1answer
35 views

LASSO or other regularized regression with censored (missing) data

Here is my problem. I am looking at various time series curves. Let's call them total spend aggregated over all customers on various products versus time. At any given time, I want to predict the ...
1
vote
1answer
37 views

Is it necessary to plot histogram of dependent variable before running simple linear regression?

I was working on an assignment. The data set was really simple, only consisting one independent variable $y$ and dependent variable $x$. Someone suggested me plot a histogram of $y$ before running ...
1
vote
0answers
67 views

Joint posterior HPD region for the coefficients of the normal linear model

This problem appear in an exam put by Chris Sims (3): http://sims.princeton.edu/yftp/emet04/ConfidenceCredibilityEx.pdf Suppose the following model: $y=\beta_1 +\beta_2 X_2+\beta_1 X_3 +\epsilon$ ...
4
votes
2answers
73 views

Two simple questions regarding GLM

I'm currently doing a modelling project. However, I haven't taken a bunch of statistics classes, so I have to teach myself generalized linear models. I'm reading Generalized Linear Models for ...
2
votes
0answers
37 views

What is the best way to simulate data for a linear regression model?

I am concerned with simulating data for a linear regression model. I need to control the means, variances, and correlations (covariances) between the predictors and the criterion variable. In ...
1
vote
1answer
60 views

Closed form posteriors for a simple bivariate Bayesian regression

I'm analyzing a simple linear regression $Y_{i}$~$a+b*X_{i}+e_{i}$, with $e$ being normally distributed with known variance and where I have normal priors on $a$ and $b$. I'm trying to piece together ...
0
votes
1answer
42 views

Inconsistent x-y relationship from paired t-test and linear regression

I am analyzing an experiment comparing the effect of treatment A vs. B on the matched subject. Here are the measurements on 34 subjects: ...
1
vote
1answer
63 views

How to capture & present lm model output from R

After running iterations of lm() in R, I am now stuck with which components of the model's output to present and how to present them. I know that the $R^{2}$ value, ...
0
votes
0answers
30 views

center variable separately for each factor in linear mixed model?

I am working on a relatively simple mixed model where I have two continuous predictors with an interaction term and three sites. I am treating the two predictors as fixed effects and the site as ...
0
votes
0answers
41 views

Groups in linear regression with different intercepts. How do I find the differing variable?

This is more of a conceptual question. I have a coefficient estimate of .80 in a linear regression model with one IV and one dependent variable. However, plotting the data I see distinct groups, ...
2
votes
0answers
19 views

Number of significant linear predictors if predictors are not independent?

I would like to determine which of a set of candidate predictors $\{x_1, x_2,\ldots, x_n\}$ are significantly relevant to the linear prediction of $y$. Typically, one can compare a full model ...
1
vote
0answers
28 views

Which statistics to use calculating prediction interval of dummy linear regression?

I have performed a linear regression and found a model of the form: $$ \hat{Y} = \alpha + \beta_1 x+ \delta_{high} + \delta_{low} + \epsilon\\ $$ Where: $\beta_1$ is a continuously distributed ...
11
votes
2answers
147 views

Bayesian lasso vs ordinary lasso

Different implementation software are available for lasso. I know a lot discussed about bayesian approach vs frequentist approach in different forums. My question is very specific to lasso - What are ...
0
votes
0answers
12 views

Achieving high recall for smaller class in unbalanced linear svm

I have an svm-related question. I have an unbalanced dataset, meaning classA could be 1/10 to 1/35 of classB. Well I am interested in getting a linear svm which would separate the data and would ...
0
votes
0answers
14 views

Fitting a Mixed Model with Random and Repeated effects in SAS

I have want to fit a linear regression with repeated measures and random effects. The data come from clinical observations. In CT images The dependent variable is the diameter of a lymph node lesion ...
0
votes
0answers
27 views

dichotomizing a predictor variable [duplicate]

Does dichotomizing a predictor variable always reduce the power in a linear regression model? We have a normal distribution for a predictor and then have sampled just from the high and low parts of ...
0
votes
0answers
54 views

Linear model for data that follow gaussian distribution

I have a question about linear regression. We have the linear regression of input data $(X,Y)=((x_1,y_1),(x_2,y_2)...(x_n,y_n))$ is $$F=aX+b$$ a,b are factors of the linear line, $y_i$ is {-1,1}. ...
0
votes
0answers
18 views

Understanding Differential Expression Analysis in Microarray Experiments

Can someone please provide me a simple explanation of how differential gene expression analysis works? I know that this method is described in [1] and used in the R package limma. [1] Smyth, Gordon ...
0
votes
1answer
43 views

How to show linear model corresponds to exponential family

I am confronted with the exercise below. I have no given solution, so I hope someone can tell me whether my solution is right or wrong. I want to show the deterministic linear model $\quad ...
7
votes
1answer
136 views

Obtaining an estimator for z given an estimator for log z

As per gung's advice in Getting the equation from R's lm when using a product, I am starting a new thread for this question. I have a model $\widehat{\log z} = a + bx + cy + dxy$ for random ...
3
votes
1answer
38 views

Getting the equation from R's lm when using a product

Similar to this question: How to translate the results from lm() to an equation? in which the top voted answer said how to get the form of an equation from ...
0
votes
1answer
35 views

Question about using a multiplicative dummy variable

In many econometrics model, the changes in the response variables in certain intervals are more difficult than other intervals. But I believe this is often not considered when estimating the model. ...
2
votes
1answer
44 views

Boundary/threshold test for regression-type scatter plot

I am looking for a way to test weather a boundary threshold exists in a physiological response--a sample of the data is plotted below. My hypothesis is that the X-variable imposes a physiological ...
4
votes
2answers
180 views

cubic relationship after linear relationship

Sorry for my title, but I really don't know how to describe this question. I am fitting a linear regression in R now, and I find that there is one parameter showing linear relationship before certain ...
0
votes
1answer
60 views

How to treat x=0, y=0 in a linear model with no intercept?

Very often in the research we want to establish a linear relationship without intercept: $y=\beta x + \epsilon$ and the sample has many double zero observations $x=0, y=0$. I am wondering how to deal ...
7
votes
4answers
332 views

Is using deciles to find correlation a statistically valid approach?

I have a sample of 1,449 data points that are not correlated (r-squared 0.006). When analyzing the data, I discovered that by splitting the independent variable values into positive and negative ...
0
votes
0answers
31 views

In linear regression the prediction error range is increasing while the the mean of the error is decreasing

I conducted a linear regression on a large and highly skewed data set that contain 80 variables,about 1.0 Million of users that didn't spent money and about 15k of users that spend different amount of ...
0
votes
0answers
37 views

Linear model with categorical dependent variable

I need to identify relationships between multiple 'counting' independent variables (representing numbers of amino acids in a protein sequence) and one ordered categorical dependent variable (an ...
0
votes
0answers
41 views

Within-subject and between-subject fixed effects in mixed model

I've been trying to analyze some data using mixed models but I have some troubles to understand how should I include both within-subject and between-subject fixed effects in such models. Let's ...
2
votes
1answer
35 views

Coefficient of Determination: For the perimeter and area of a square: Why different?

When calculating the coefficient of determination for a square, why is it that if you use the data set for the side length of as X= (1,2,3,4) and the perimeter as Y=(4,8,12,16) the Coefficient of ...