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1 vote
1 answer
201 views

Which regression model would you choose?

Which regression model would you choose to model the following flood damage data? The variables are x1=water height, x2=dike height and x3=flood damage. The following plot shows how the flood damages ...
Sjafnargata's user avatar
0 votes
1 answer
25 views

How do I select a KNN model?

I am considering methods of selecting an optimal K Nearest Neighbors model for classifying a pixel as representing a refugee's blue tarp or not. See https://www.kaggle.com/datasets/billbasener/pixel-...
Tom Lever's user avatar
  • 121
0 votes
0 answers
32 views

Theoretical question about GAM (generalized additive models)

I'm new to GAM so please be patient with me. This is a theoretical question rather than a coding question. I have a model as follows: response variable (y) = insect abundance; Disturbance type (...
Bugguy's user avatar
  • 1
1 vote
2 answers
739 views

How does the Bayesian Information Criterion work for model selection? [closed]

I am aware that we can use the BIC values from different models in order to determine which model predicts the data best. However, I'm a little confused about the criteria used to determine which ...
john connor's user avatar
1 vote
1 answer
37 views

Why this regression model with one predictor don't work?

I have this R script. I want to estimate the coefficient of the dependent variable Y based on several regression. ...
StatRquest's user avatar
2 votes
1 answer
100 views

Why model order selection is a big problem in statistics?

I’m learning statistical signal processing for my studies. I was doing a bit of literature review on model order selection and I didn’t want to miss out on techniques that I might not have seen. I ...
CfourPiO's user avatar
  • 235
1 vote
0 answers
22 views

Does changing model due to overdispersion/underdispersion results in forking?

This is related to the post How much do we know about p-hacking "in the wild"?. The post does not clearly delineate the boundary between forking or not forking to me. Suppose I have a count ...
user45765's user avatar
  • 1,445
19 votes
3 answers
2k views

Widespread overfitting in health domain research?

I was reading about flaws with model selection techniques such as elimination based on significance and backwards selection via AIC (or similar) in the context of regression leading to inflated ...
JED HK's user avatar
  • 409
4 votes
1 answer
105 views

Is it possible that GEE and mixed effect GLM give contradicting answers? If so, which one should be trusted?

Is it possible that GEE and mixed effect GLM give contradictive answers in significance of covariates? I assume both GEE and GLM selects same covariates. If so, which one should be trusted? From ...
user45765's user avatar
  • 1,445
0 votes
0 answers
70 views

Best approach for AIC model selection?

I am doing a study where I am trying to model how different factors affect polar bear movement. I would like to conduct model selection using AIC. So far, I believe I have two options:   1)    Put ...
Cam's user avatar
  • 151
0 votes
0 answers
19 views

model to explore correlation of pollution long-term exposure with genetic mutation rates

I have pollution data of several US cities, as example NY, Boston, and Chicago. I need to ...
cccnrc's user avatar
  • 229
1 vote
0 answers
51 views

Why does the best fit model (lower AIC) yield higher p values than models with higher AIC? [closed]

Background: I am running a model selection in R that includes 1, 2, and 3-covariate models. Each model aims to determine the effect of environmental covariates in the occupancy of different species in ...
Max Amaya's user avatar
3 votes
1 answer
82 views

Can I use AIC for path models and non-path models?

I am testing competing hypotheses where one hypothesis contains a mediation effects that can be modeled using a path model. The other hypothesis does not include a mediation effect and therefore can ...
Leo Ohyama's user avatar
0 votes
1 answer
157 views

ANOVA for comparing same linear models

I have trained two linear regressor models with the same response $Y$ and the same features $x_1$ and $x_2$, they are basically the same model, however only the training data differs: in model1 data ...
dm_reader's user avatar
2 votes
1 answer
120 views

Which choice model to analyse my binary stated choice experiment data to estimate willingess-to-pay?

I followed the recipe of a stated-choice experiment in political science https://doi.org/10.1093/pan/mpt024 (they call it "conjoint" but I think this term is debated). In the end I made the ...
canIchangethis's user avatar

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