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Questions tagged [goodness-of-fit]

Goodness of fit tests indicate whether or not it is reasonable to assume that a random sample comes from a specific distribution.

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Fitting a Multivariate Ornstein-Uhlenbeck Process to Data

I have multivariate time series data (100 dimensions or more) and wish to test the hypothesis that the dynamics follow a Langevin equation. A simple case is the Ornstein-Uhlenbeck process, how can one ...
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Why my Rho-square on Multinomial Logit Model (McFadden) so small?

When I'm using MNL, and try to find my rho square, it's found out to be so small. It is $0.0139$. For a good fit model, the rho square has to be between $0.2$-$0.4$. Is there any reason why it's so ...
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Where can I find a Kolmogorov-Smirnov critical value table for an F-distribution? [closed]

I have developed an Excel model for a one-sample Kolmogorov-Smirnov test for an F-distribution. I have the K-S test statistic, but no CV to compare it to. If anyone knows of an online table of ...
Jim Robison's user avatar
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Why in ordinary linear regression is no global test for lack of model fit unless there are replicate observations at various settings of X?

I read this quote from Regression Modelling Strategies. In ordinary linear regression there is no global test for lack of model fit unless there are replicate observations at various settings of X. ...
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Uncertainties when fitting an image

I know how to fit a straight line to a set of 2d points with uncertainties on both coordinates, in order to obtain estimators, goodness-of-fit, and uncertainties - see for instance Press & ...
Mister Mak's user avatar
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Cumulative Residual Plots for GLM Goodness-of-Fit Tests

I wanted to ask about the cumulative residuals (CURE) plots for testing the goodness of fit test for negative binomial regression. CURE plot has been a standard in traffic crash frequency modeling for ...
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Why GLM fit is different from direct fit using logistic function [closed]

I found in my data that a direct fit using the logistic function gives a different and better (R^2) fit than GLM fit using binomial distribution with logit link function. I was naively expecting the ...
santelus's user avatar
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Goodness of fit test binomial random variables without "compensation"

Let $N_{1}, N_{2}\in\mathbb{N}^{+}$ and random variables $X_{1}\sim B(N_{1},p_{1}),X_{2}\sim B(N_{2},p_{2})$ with null hypothesis $H_{0}:p_{1}=p_{1,0}, p_{2}=p_{2,0}$. I would like to apply a GoF test ...
CorrieElba's user avatar
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1 answer
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What does it mean when a CFA model improves drastically by ommiting a factor?

I am trying to fit a CFA model with four factors (say F1 with 4 indicators, F2 with 6 indicators, F3 with 3 indicators and F4 with 5 indicators) in Amos. Each indicator is computed by summation of ...
M. Er's user avatar
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Moment Ratios and L Moment Ratios:

I want to know the difference between moment ratio diagrams and L moment ratio diagrams. As I understand the moment ratio diagram serve the purpose of detecting the type of probability density ...
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Understanding $\chi^2$ in plain language [closed]

Suppose I was trying to explain what $\chi^2$ is and why it's important to my grandma. I want to give core intuition to this formula: $$\chi^2 = \sum_{i}\frac{(O_i-E_i)^2}{E_i}$$ I would tell her ...
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Sample Size for Adaptive Lasso

Be gentle, I'm learning here. I have a fairly simple adaptive lasso regression that I'm trying to test for a minimum sample size. I used cross-validated mean squared error as the "score" of ...
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How to calculate AIC of a spatial panel model in R?

This may be a better question for Stack Overflow, but I think a statistics answer may be warranted here: I have built some spatial panel models in R using the ...
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external internal validation and chi square

The internal test set, created from 20 percent of the train data set, consists of 'a' and 'b' labels. I take the 'a' labels from the internal test and combine them with the 'c' group of another ...
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Poor RMSEA/Fit for Simple Poisson Regression

I am running a simple Poisson regression. $X$ = time, $Y$ = count data. This is a huge dataset with many years. There is significance between $X$ and $Y$. But model shows poor fit via high RMSEA value....
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How well does my model fit? Specifying a null-model in non-linear mixed models

I want to fit a model y ~ b * exp(-exp(a) * x), but including a random effect, with this data: ...
quak's user avatar
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How to determine goodness-of-fit between non-parametric 2d-datasets

Lets say I have a set of paired x' and y' values and I have a N sets of reference values also consisting of paired x and y values. I would like to determine which reference set best matches by x'y' ...
James London's user avatar
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1 answer
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Use of weights in non-linear least square fitting

I would like to have your suggestions and help concerning my problem. I have images generated on a position sensitive detector. The signal for each pixels corresponds to the amount of 'particles' ...
toto's user avatar
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Deriving Sample version of Anderson Darling test statistic from the theoretical version

In literature, I have seen two types of Anderson-Darling test statistic. One is expressed as $A_T^2 = n\int_{-\infty}^{\infty}\frac{(F_n(x)-F(x))^2}{F(x)(1-F(x))}dF(x)$ and the other is given by $A_s^...
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Error metric for regression of count data: Poisson Deviance or Mean Square Error?

I would like to understand what difference it makes, if I use, for example, either Mean Square Error or Poisson Deviance as error metric/loss function for a regression of count data. Are there any a-...
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3 votes
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Appropriate test to use when each sample is a permutation from $S_k$

Suppose I have a dataset $x_1, \ldots, x_n$ where each $x_i$ is a permutation of $\{1, \ldots, k\}$. [For example, if $k=4$ the data might be $x_1 = (2, 1, 3, 4)$, $x_2 = (3, 2, 4, 1)$, $x_3 = (4, 3, ...
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Comparing $R^2$ values that measure different predictions

I have a question regarding $R^2$. Say, a model A predicts $y$ based on $x$, and a model B predicts $x$ based on y. I want to test which model is a better fit to the data. Since model A predicts $y$, ...
Erik's user avatar
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Goodness of fit in GLM produces NANs

I have a GLM model which has a quadratic term and looks like this. ...
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What is the number of "explanatory variables" in the adjusted R2 formula

I am trying to assess the goodness of fit of a surface I've developed (i.e., model predicts a variable y based on 2 variables x1 and x2). My model has 5 parameters which are estimated (and is likely ...
Erik's user avatar
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Which dependent variable is mostly impacted by predictor?

Usually one wants to identify the most important predictors (x1, x2, x3..., xn) in a regression model. My question is reversed: I have a data set that contains a risk factor risk and several outcomes ...
a.henrietty's user avatar
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Poor fitted vs. actual values

I'm using a BART model (Bayesian additive regression tree) to predict the relative risk of an outcome (21,384 observations) controlling for 388 features and I'm getting a really poor actual vs. fitted ...
Tim's user avatar
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How should MacKenzie and Bailey goodness-of-fit test be used for several models at a time in model selection?

I am running single-season occupancy models and I usually have many selected "best models" by AICc criterion. At the time, I am running MacKenzie and Bailey's (2004) goodness-of-fit test for ...
Magdalena Salas's user avatar
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255 views

Poisson regression for rare events?

Poisson regression is commonly used to analyse count data. However, when we deal with rare events it does not seem to be appropriate any more. At least, graphical criteria to assess the model fit like ...
Student's user avatar
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CFA: chi-square value is 0 but with degrees of freedom

I want to do a SEM analysis with an actor-partner interdependence model in Mplus. I managed to calculate it and everything seems right if I look at the means, SD's, ...
Axenox's user avatar
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testing difference in distributions with population values (using python)

I am looking for the best method to test for a difference between two distributions. I have data from a patient group, and my aim is to compare the distribution to a reference distribution. However, ...
Ana's user avatar
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3 votes
2 answers
362 views

Goodness-of-fit test for very skewed data [closed]

I am working with two quite large datasets (9000 obs and 3800 obs). Each observation has been grouped into 1 of 12 categories and I am looking to test if the frequency of categories in the smaller ...
Elin Sjoeholm's user avatar
2 votes
1 answer
181 views

Negative Binomial Regression Model - Effect of Removing Significant Covariates

I have been dabbling in NB regression for less than a year now. I have applied the well known g.o.f. tests. Lately I started using the Conditional Moment (CM) test, described in Cameron and Trivedi ...
Barton's user avatar
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1 answer
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Fitting data with a beta distribution using fitdist from fitdistrplus package in R

I have a variable x that corresponds to data from a database. I've been trying to find the best distribution to fit it and looking at the histogram I figured either a normal, weibull or logistic ...
Ismael ancona's user avatar
2 votes
2 answers
70 views

Importance of goodness of fit in Hypothesis testing

I am struggling with one question. Is goodness of fit of a model necessary when your purpose is to test hypothesis regarding a coefficient? To be specific, I am regressing formal credit access on ...
Rupon's user avatar
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What is this nonparametric goodness-of-fit test?

I wrote down a goodness-of-fit test that I have not seen before. However, it is quite elementary and has many applications, so I bet it must have been known. Could someone tell me its name? Setup. The ...
Student's user avatar
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1 answer
91 views

obtaining a goodness of fit indices for an analysis with tweedie distribution

I performed an analysis specifying a dependent variable with a tweedie distribution using the glmmTMB package in R. I got several fit indices, specifically: AIC, BIC, Logliklihood. What is the most ...
Lior's user avatar
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3 votes
1 answer
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Should Kullback-Leibler as an R2 value be large or small for better goodness-of-fit

I am trying to use the Kullback-Leibler as an R2 value for goodnes-of-fit for GLM models. The R package performance defines their function as: ...
simpson's user avatar
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Variations of Correlation Coefficient of Simple Linear Regression with Estimators [duplicate]

Suppose we are using an Ordinary Least Squares (OLS) estimator of $\alpha_{0}$ and $\alpha_{1}$ for the simple linear regression below: $$ H_{i} = \alpha_{0} + \alpha_{1}X_{i} + \epsilon_{i} $$ How ...
Plesiozaurus's user avatar
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52 views

C-statistic (or AUC) for fractional logistic regression (i.e. continuous regression)

I have proportional data to which I have fit a logistic regression (i.e. fractional logistic regression). The statistician in our group wants me to provide a c-statistic for the regression. My ...
Brandon's user avatar
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2 votes
1 answer
485 views

Goodness of fit of structural equation modelling

I am currently working on a structural equation modeling project using the lavaan package in R. The model satisfied all the goodness of fit tests (GFI, AGFI, CFI, ...
Suba's user avatar
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Can I move on to the next level (test) of invariance when my fit gets better?

I am running a group invariance test. The data consists of data from students from grades 5 and 6 for one school (School A) and only from grade 5 in another school (School B). I have already run group ...
EmH's user avatar
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Interpretation of Anderson–Darling test

Assume that I am using Anderson–Darling test to evaluate whether a given sample of data is drawn from a normal distribution with some mean and standard deviation. If you accept the null hypothesis in ...
Barbab's user avatar
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Yes or no: is Pearson’s r is a measure of goodness of fit to an affine function? [duplicate]

Is the statement "Pearson’s r is a measure of goodness of fit to an affine function" literally true? Why or why not?
BigMistake's user avatar
1 vote
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19 views

Is it possible average an information criterion across models?

Is it possible to take the average of information criterion like the AIC? For my model comparison, I have 24 different models. I use 4 different GARCH models each with 6 different distributions for ...
Hello there's user avatar
0 votes
0 answers
80 views

How Anderson-Darling test with Braun's method works in R?

I generally work with skewed and heavy-tailed lifetime distributions, so I need to check the goodness-of-fit of certain data to such distributions. After some exploration, I came to know that the AD ...
DevD's user avatar
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0 answers
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Easy goodness of fit tests when using svyolr package (ordered logit regression on complex survey data)?

for a uni project I am running an ordered logit regression on survey data, using the svyolr package in R. I am looking to report some sort of goodness of fit for the model but am struggling to find ...
Ollie's user avatar
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3 votes
1 answer
385 views

Pearson chi squared test vs deviance test in GLM

From my understanding, both Pearson chi squared test and deviance test can be used to assess the goodness of fit for GLM, but they have different alternative hypotheses. For the Pearson chi-squared ...
user344849's user avatar
1 vote
1 answer
188 views

Comparing the goodness of fit for multiple GLS models applied to different data sets

I fitted simple linear models to several (6) data sets of different sizes, using GLS. All models have the same predictors (but the coefficients are different). I would like to compare the goodness of ...
soungalo's user avatar
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0 answers
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Is Pearson's chi-squared appropriate for models with low deviance explained?

I'm working on fitting a binomial GLM using LASSO in R (package glmnet). My response variable is a proportion which is generated using count data (successes and failures). The main purpose of my model ...
pfadenhw's user avatar
0 votes
2 answers
42 views

Is goodness-of-fit a reasonable way to test the usefulness of correlated precitors

Under a hypothesis testing framework, I would like to model $Y \sim X_1 + X_2 + Z$ where X_1 and X_2 are two related, likely ...
Jeremy's user avatar
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