0
votes
0answers
4 views

Weighted Least Squares with Standardized Coefficients

I want to understand how weighted least squares regressions work to implement it in a more complex context. I think I'm a good step into that process, but I'm still wondering what the correct way to ...
1
vote
2answers
21 views

Factor or No-factor

I am performing linear regression in R and I have a variable called diversityscore which is a value ranging from 1 to 10 indicating #activities a user performs with 1 meaning one activity to 10 ...
2
votes
1answer
59 views

What kind of model can I try to fit in this plot?

I have a plot like this. I wish to apply a model to this, however, I guess a linear regression model won't work on this. What I did was plot it on logarithm x and logarithm y axis as well but it ...
2
votes
1answer
63 views

Can we skip the lower order terms in interactions? [duplicate]

This question is about three-way interaction and the possibility of applying without second lower terms with keeping the main variables in the equation not like the other questions. In fact the other ...
0
votes
0answers
8 views

Using Mantel to explore relationship between geographic distance and a multivariate character

I'm working with bird songs. A song is composed of many vocal parameters [highest frequency (Hz), lower frequency(Hz), bandwidth(Hz), duration (s), number of notes, and son on....] I'm interested in ...
0
votes
0answers
43 views

Determining Relative Weights

I am looking for some recommendations and more specifics about how to do the following: Objective: To determine the weights of a number of stock valuation metrics. I am looking at doing this across ...
0
votes
1answer
19 views

lm() producing many NAs for coefficients

I am trying to run a regression using about 80 independent variables. The problem is that the last 20+ coefficients return NA. If I condense the range of data to within 60, I get coefficients for ...
0
votes
3answers
42 views

Covariate no longer significant after inclusion of interaction term

I'm trying to interpret some results here, and just want to make sure that my logic is sound. I'm predicting a binary outcome with a categorical predictor (gene level coded as 0, 1, or 2 dependant on ...
2
votes
0answers
30 views

Is two years enough for panel data analysis?

I have around 800 companies for only two years period. However, around 200 of them have only one year observation. Is it still possible to conduct panel data analysis with such data Thank you
0
votes
1answer
27 views

Find the amount of variation due to another covariate

I'm trying to explain a binary outcome (cardiovascular disease) with a categorical predictor (gene level, coded as 0, 1, or 2 depending on the number of risk alleles present). I'm trying to determine ...
1
vote
3answers
43 views

Correlation using Logistic Regression and Pearson

I am so sorry, I am beginner in statistic analysis, I have project using R to analyze the correlation between dependent variables and independents variables. In this case I have two dependent ...
1
vote
0answers
13 views

Test if a slope falls within a back-transformed (log) prediction interval

I'm trying to test the hypothesis that the relationship (slope) between second molar tooth size and overall molar tooth size is 0.33 (in species of rodents), using generalized least squares regression ...
0
votes
1answer
28 views

Compare regression slopes of repeated measures linear regression

In my design, I have two groups of subjects and every subject is tested in four different conditions. So, I have a within-subject factor ('span_num', which ranges from 0 to 3) and a between-subject ...
-4
votes
0answers
90 views

Exploratory regression analysis for data with missing values

Recently I have performed an exploratory regression analysis, using lavaan R package and observed the following output with some warning messages in it. I have the ...
1
vote
0answers
13 views

How to compare fit of discrete process with discrete underlying process?

I am basically looking for an equivalent to something like an $\mathbb{R}^2$ for a model on a dataset that is itself simply a collection of points. That is, if my data set is (trivial example): ...
0
votes
0answers
37 views

Propensity to purchase using regression analysis in R [closed]

I have a dataset with a sample snapshot of it looking like this: ...
0
votes
0answers
9 views

In practice, how is the penalisation matrix for splines, created by smoothCon (package mgcv), specified?

Evaluating a smooth object with smoothCon provides, besides several other things, the ordinary "untouched" spline bases ...
1
vote
1answer
21 views

Is it possible to measure the independent variable with part of the dependent variable

I have Beta as my independent variable and Economic value added (EVA) as my dependent variable. To calculate EVA I need to use Cost of capital and to calculate that I have to use Beta, so is it ...
0
votes
0answers
24 views

How to interpret residual plots from time series regression

I am doing a time series regression between 2 variables. I used the dynlm library in R. I'm trying to understand how to interpret the results. Could you please point out where I am getting it wrong: ...
0
votes
0answers
30 views

What types of statistical analysis technique available to compare two different time series [closed]

I am currently looking for suggestion to compare or study the two different period time series like sales in 2000 and 2001. As it is sales of the same product and i would like to compare those two ...
1
vote
0answers
16 views

geepack: parameter estimates change sign depending on correlation structure

I'm working on a dataset with the following variables: ...
0
votes
1answer
38 views

tease out significance

Say I have search data like this AvgCost QualityScore SearchShare 3.12 6 0.6364 Where AvgCost is a ...
1
vote
1answer
30 views

Treating multiple observations per object

I am working on a project whose aim is to analyze the relationship between machine elements and their price. My data consists of thousands of machine elements, their price, as well as technical and ...
0
votes
0answers
6 views

R mhurdle with same 2 predictors in 2 separate hurdles

My outcomes are zero-inflated but otherwise normal. I want to propose a model in which the very same predictors determine both whether the value is zero or non-zero, and separately from that, if ...
0
votes
1answer
38 views

Interpretation of polynomial regression output in R

I performed a polynomial regression using the following formula: lm(deviance ~ poly(myDF$distance,3,raw=T)) However, the summary output states that only the ...
0
votes
1answer
31 views

Hodrick-Prescott derivation in lay terms

I am currently working with the Hodrick-Prescott filter. I would like to understand the equation in lay terms.
0
votes
0answers
13 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 ...
1
vote
1answer
45 views

What are 'aliased coefficients'?

While building a regression model in R (lm), I am frequently getting this message ...
0
votes
1answer
23 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 ...
0
votes
0answers
33 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 ...
0
votes
1answer
21 views

R regression with categorical response variable

I have four variables, two are categorical and two are numeric: ...
0
votes
0answers
24 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 ...
0
votes
1answer
54 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 ...
0
votes
0answers
13 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 ...
0
votes
0answers
25 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 ...
0
votes
1answer
37 views

Constrained and Weighted Regression

I'd like to modify the answer to this question to allow weighted observations. I think all I need to do is weight the inputs X and Y. X = w * X Y = w * Y the ...
2
votes
0answers
14 views

if the suggested power transformation by spread level plot is 1, does the model have constant variance?

I am working on checking for constant variance in linear models and checking by looking at the plot of studentized residuals with fitted values. My data set via the plot looks to have a constant ...
2
votes
3answers
56 views

Test model coefficient (regression slope) against some value

In R, when I have a (generalized) linear model (lm, glm, gls, ...
1
vote
1answer
33 views

Over represented gender in linear modelling data

I am fitting a model to some sales data and looking to accurately represent male/female behaviour (e.g basket analysis). For example, I know the proportion of females/males in the population buying ...
2
votes
0answers
37 views

How are the standard errors computed for the fitted values from a logistic regression with parameter 'response' in R?

I am looking for the equation for the se.fit values when using logistic regression in R. I have seen this answer - How are the standard errors computed for the fitted values from a logistic ...
1
vote
1answer
25 views

How to Find Adjusted $R^2$ or $R^2$ from Lasso and Ridge regression model

How do I find the adjusted $R^2$ (or $r^2$) from Lasso and Ridge regression? I used the glmnet package. For instance if I have this code so far.... ...
3
votes
1answer
68 views

Is there an R package for MCMC estimation of Generalized Method of Moments?

I'm looking for an R package (or a combination of packages) that would allow me to perform MCMC estimation of a GMM model, with a user-specified moments function. I've looked at the CRAN Bayesian ...
1
vote
0answers
21 views

Applying ARMAX model from r output

I'm trying to apply R output to generate a scenario using external data, I'm not sure how exactly to use the coefficients in each from the R output. I have an ARMAX(1, 1) model Coefficient of AR1: ...
1
vote
0answers
33 views

Multiple covariates for each fixed effect

I'm analyzing data from a classical intervention design. Subjects were divided into groups, undertaking different interventions. Each subject was measured using the same tests before and after the ...
0
votes
1answer
56 views

R - Confused on Residual Terminology

Root mean square error residual sum of squares residual standard error mean squared error test error I thought I used to understand these terms but the more I do statistic problems the more I have ...
0
votes
0answers
38 views

How to preform non-parametric bayesian based regression (predictions) in R?

I am working on some non-parametric bayesian based predictive analysis using R. I have a set of data which denotes various parameters of an online transaction. Based on these parameters I want to ...
0
votes
0answers
23 views

Assessing the accuracy of zero-inflated beta regression models

I have fitted a zero-inflated beta regression model to my data in R, using the gamlss package. However, I am unsure of how to assess the fit of the model to my data, i.e. finding a coefficient of ...
0
votes
0answers
27 views

linear or poisson regression for monsoon onset

I was interested to know if I have historical data of onset of monsoon every year (where onset for each year is in Julian day) and I want to do a regression of onset against time to study whether the ...
0
votes
0answers
52 views

Is this a case for an ordinal logistic regression? Problems interpreting output

I'm a beginner in statistics and R, sorry if this question may seem trivial. I've collected data measuring several different parameters in 40 subjects at two time-points (t1 and t2). There are 3 main ...