Questions tagged [log-linear]
The log-linear model is a form of Poisson regression that allows for the analysis of multi-way contingency tables.
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Interpretation coefficient for log ratio as dependent variable and independent variable is 0-1 (percentage) [duplicate]
I'm struggling to follow the interpretation of the log coefficients. Union density represents the share of unionized households it is scaled between 0-1. The coefficient for union density is in my ...
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Why shows a two variable $\chi^2$-test a significant p-value while a log linear analysis on the same data does not?
I did an experiment to look at the influence of two categorial variables onto a categorial output. The input variables were T and ...
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Test to compare multiple contingency tables
I have three contingency tables with the variables month and region that contain the frequency of the sighting of a particular bird. Additionally, the tables differ only by counting frequencies from ...
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Interpretation of proportion coefficient
I know that I should be able to work this out but I am struggling. My dependent variable is a log variable (call it y) and my independent variable is a proportion that takes a value between 0 and 1 (...
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Multicollinearity in mixed log-linear model
I am currently running a mixed log-linear model which is in this form:
Log yit = Xit + X2it + (1|individu)
I suspect a multicollinearity ( cor (Xit , X2it) close to 1 ). Do you think it makes sense to ...
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Power for hierarchical loglinear model
Can anyone point me in the right direction for doing sample size/power calculations for hierarchical log-linear analysis of nominal (frequencies) data? Would I get in trouble with reviewers for just ...
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Contingency analysis of a 3x3 table via Chi2, log-linear and Poisson GLM - how to interpret this result?
I have a dataset describing age of wine in 3 classes of quality.
...
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Poisson Regression and homogenous association
Let's consider a log-linear Poisson model with three variables A, F, C such that the model is a homogeneous line-by-line association model in AF.
How on earth the maximum likelihood equations are, for ...
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Loglinear model = Ising model?
Is it true that an hierarchical log-linear model of order two which includes all the interactions of order two between the binary variables X1, . Xp is an Ising model? I saw this on a online ...
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Collapsibility Conditions for Multiway Tables
Why is the WX conditional association the same as the WX marginal association in log linear model (WX, XYZ) (four-way table) and not in the log linear model (WX, WZ, XY, YZ)?
I saw on the internet to ...
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"Percent change" interpretation when we $\log$ the expected value instead of taking the expected value of the $\log?$
When we take the log of the $y$ variable of a regression and then fit the OLS estimator via $(X^TX)^{-1}X^T\log(y)$, we can interpret the regression in terms of percent change in $y$.
However, this ...
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Help determining model and interpreting coefficients of log-linear relationship
I am trying to determine if the hospital I work at should open a new unit for admissions. I intend to do this by correlating patient assigned unit and length of stay in days.
So far, I have determined ...
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Compressing vectors by using log-linear modeling?
I have $k$ vectors, each consisting of $2^n$ positive reals adding up to 1, and I'd like to compress them by only saving $n$ reals per vector.
One approach is a no-interactions log-linear model to ...
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Resources to help conduct a log linear (logit) model in spss
Does anyone know of any resource about how to conduct a loglinear (logit) analysis in spss? There are some youtube videos but not specifically about the logit one.
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Choosing the best type of analysis for my variables and objectives
I am struggling to identify the best analysis for my design. My two independent variables are binary (dichotomous) and my dependent variable is also binary (dichotomous). The goal is to find whether ...
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Ranking log-linear distributions and the Lucas numbers
The wikipedia page on rank-size distributions claims:
"When any log-linear factor is ranked, the ranks follow the Lucas numbers, which consist of the sequentially additive numbers 1, 3, 4, 7, 11,...
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Calculation of the standard deviation of the power in dB
I wanted to find out the stability of my system so for that i calculated standard deviation of power samples data which is in dB but I am not sure whether i have used correct formula or not.
As far as ...
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Iterative proportional fitting with constraints
I am trying to determine if it is possible to conduct iterative proportional fitting with some constraints. To give a dummy example of my goal:
Say I had data for two towns, A and B, on the ice cream ...
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Why does log-linear analysis seem to ignore the Poisson regression equidispersion assumption?
As far as I understand it, log-linear analysis is based on the use of a Poisson regression. This is what I understood from various online resources, like this online tutorial or this text whose intro ...
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How do I choose which variable transformation (logY~logX/logY~X/etc)? [closed]
I'm doing a linear regression assignment using a variable transformation using R.
and I have several questions.
What is the criteria of choosing which type of variable transformation?
We've learnt &...
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Visualizing relationships in log-link/exponential distribution models by placing the linear predictor on the Y axis?
I'm visualizing results from a negative binomial regression. I don't want to the graph of Y vs X to look exponential, I want it to look linear. In SPSS, the value provided for the linear predictor is ...
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How to correctly perform a goodness-of-fit test for a contingency table (two-way, three-way, or more), in situations other than independence testing?
Let's say I have the following table from a sample of 462 people:
Gender
Happy
Meh
Sad
Men
70
32
120
Women
100
30
110
I don't want to test it against the hypothesis of independence, but against ...
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taking log of a variable with values of 0 [duplicate]
I have an outcome variable 'expenditure' which I believe may be non-linear in nature so I am running a log-linear regression after taking log of the variable. However, there are values under ...
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Clarification on likelihood maximisation
From Eisenstein Natural Language Processing textbook, a discriminative log-linear model is defined as $$p(y|x,\theta) = \frac{\exp(\theta^Tf(x,y))}{\sum_{y'} \exp(\theta^Tf(x,y'))}$$
To estimate the ...
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Log-linear and GLM (Poisson) regression
I am afraid I am asking a stupid question... but...
I would like to study the spending (my outcome variable) of a company by department, number of staff, activity, etc. I have collected my data and ...
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Using Log-Linear Regression to calculate the growth rate
I am learning the formula of growth rate and how to calculate this
Growth rate is $y = a * (1+x) ^ b$
Log-linear regression: $log y = log_a + b * log (1+x)$
Then b is considered as coefficient
What I ...
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What is the best way to test of draws ( 10,000 unique possibilities) from multiple sample are random?
say I have 6 people drawing from their own box, each box contains 10,000 unique barcodes. Now at the end of the experiment each person has drawn roughly 10-20 barcodes. How do I test if the barcodes ...
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log-linear model in R under multinomial scheme
I am trying to fit a log-linear model. In short, we can fit a log-linear model when family=poisson in R. But when we condition on N, we have multinomial ...
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Scale Parameter in a Log-Linear Accelerated Failure Time Model
Let the logarithm of the random varible $T_i$, associated with the lifetime of the $i$th individual in a survival study, follow the disitribution
$$log(T_i) = \mu + X_i\beta + \sigma\epsilon_i$$
with $...
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Mean Log10-Linear regression
In field experiment I have gathered data for X and Y with the aim to fit a regression and use X to predict Y in the future. Based on physics, I know the relationship should be of the form
$y = 10^{a \...
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How do you change log-linear transformed prediction interval values for a regression back to original scale in r?
I have a simple regression model where I needed to log-transform the dependent variable because the model residuals were non-normal. Now my model is ok in that respect. So, I ran the model. But, ...
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Differing AAPC and Confidence Intervals Using the Joinpoint Regression Trend Analysis Software vs R
Let's say I have a data-set with trend data looking at an adjusted rate by year from 1980-2000, with a standard error associated with it:
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Does benfords law imply a log scale for the distribution?
We see Benfords Law in a lot of real world data sets, with the general derivation that if things are distributed symmetrically on a log scale, then the law holds. However, it's not obvious to me:
Why ...
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Why AIC for log-linear model in glm returns Inf?
I am trying to calculate the AIC for log-linear model in R, but i get Inf as a result. The model aim is to predict sales in euros based on some variables.
As far as ...
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Can't find loglinear model's corresponding logistic regression model
I have the loglinear model with parameters x, y, z, v, xy, xv, and z*v. As far as i understand there should exist a logistic regression model that essentially is equivalent to this, using v as ...
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Can $G^2$ statistic in log-linear model for contingency tables be negative?
Can $G^2$ statistic of log-linear (unsaturated) model in contingency tables be negative? Since saturated model with perfect fit has $G^2=0$ I don't think the unsaturated models can get negative $G^2$. ...
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log-linear modelling: transforming y variable
I am conducting a study on graphical log-linear modelling and my aim is to fit a log-linear model to data.
I am using R studio to carry out the analysis and I am using the glm function.
When first ...
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How Can I Interpretation in loglinear regressions with coefficients greater than 1
I run a loglinear regression and got dummy variable coefficient for education level bigger than one. It's also significant and my depend variable's log wage.
How would I go about to interpret the 2.21?...
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Correlation of categorical data to binomial response in R
I'm looking to analyze the correlation between a categorical input variable and a binomial response variable, but I'm not sure how to organize my data or if I'm planning the right analysis.
Here's my ...
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Mean of predicted values in a log-linear model
I run a log linear model $$\log(Y)=\alpha + \beta X + \epsilon$$
and wonder how to calculate the mean of predicted values, in the same dimension as the initial (untransformed) variable Y.
I would ...
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Log-linear fit and parameters in case of perfectly correlated variables
Here is an example case. Take the following ´data´:
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Check if dropout rates are independent for an interaction of two independent variables (one with a large amount of levels)
I am trying to analyse dropout rates in an experiment, but there are multiple issues which collide, and I don't know how to deal with them as a whole. First, find a list of those issues. Below, see a ...
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interpreting a log-log-linear model of two continous variables with or without interaction terms
I am regressing ecological distances between communities (as expressed as similarity) over their spatial and temporal distance on a regular grid of 360 sampling stations divided over six time points. ...
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Statsmodels - 'corrected predictors' on log-linear models?
I'm currently working through an econometrics book , and in the section about log linear models it is stated that predictions
made with ...
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Log-linear model for contingency table with no fixed count
I have table of counts of born children with four two-level factor variables (mother smoker/nonsmoker, child born dead/alive, ..). I would like to use log-linear model to understand interactions of ...
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Help needed to Interpret ln(y) = a +b (Standardized X)
I am analysing server data and I have a scenario where I need to get the % by which Y is changed because of a unit change in X:
EDIT: I am doing a Linear Regression in Python
(and its other forms ...
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Appropriate way to visualize significance in 2x3 contingency table using mosaic plot
I've checked multiple threads about handling or visualizing contingency tables, but can't find one that can help my current question. I have a 2x3 contingency table: "group" variable has 3 levels not ...
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Interpreting log-linear model for contingency table in R
I'm looking at sample data and trying to determine whether there is any association between the height of the husband and that of the wife below. I don't fully understand what the symbolic ...
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Log-linear difference-in-differences
I am estimating several linear models using a difference-in-differences (DiD) framework. The model interacts a treatment indicator (i.e., 1 for the treatment group, 0 for the control group) and a "...
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Bivariate analysis as a basis for a subsequent analysis?
I have run across many research articles which used bivariate analysis, whose results become the basis for a subsequent analysis. For example, a Chi-squared test was used as a preliminary analysis to ...
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