Questions tagged [modeling]

This tag describes the process of creating a statistical or machine learning model. Always add a more specific tag.

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question about including an independent variable

I'm seeking advice on whether to include the independent variable 'smoking' (Yes/No) in my analysis. The objective is to examine the impact of COVID-19 on female construction workers. The outcome ...
Science11's user avatar
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1 vote
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Exploring Statistical Independence of Apartment Ownership [closed]

I've embarked on an intriguing statistical journey involving the analysis of apartment ownership among graduates, and I could really use your insights. The Central Bureau of Statistics conducted a ...
Johnny Depp's user avatar
2 votes
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22 views

Modelling consecutive Poisson point processes, where the second starts only after the first has x counts

I'd like to model a situation where there are 2 consecutive Poisson point processes with different event rates, and the second process only starts after the first process reaches a cumulative event ...
abcoxyzide's user avatar
4 votes
1 answer
67 views

Assessing the relationship between two variables

I've been trying to analyze the possible association between the number of questions done while studying and the average result of users after several testing sessions. The ...
Pedro Alonso's user avatar
1 vote
0 answers
28 views

Statistical Modelling Research Papers

My task was to make a logistic regression model for a dataset to predict a binary variable (0/1). During this process I went through all of the stages of model building, from scratch given unprocessed ...
Alex Smirnov's user avatar
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Mixed model realized value of random variable

In Andrew Gelman's book "Data Analysis using Regression and Multilevel/Hierarchical Models" , page number 258 group $j$ random intercepts $\alpha_j$ is estimated based on this expression $$\...
Sundown Brownbear's user avatar
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10 views

Modelling count from frequency

I have an empirically derived frequency curve. From the curve, I aim to model counts per unit time. The x-axis is diameter, and the y-axis the likelihood of observing the diameter per one year. I ...
Eron Raines's user avatar
6 votes
2 answers
199 views

exclude random effects component for a repeated measure

I'm analyzing a dataset on the Nurse Licensure Exam, comprising 3000 participants. (n) These 3000 participants were randomly recruited from 13 Sites across the US. (group level variable) About 40% of ...
Sundown Brownbear's user avatar
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0 answers
17 views

Approaching regression analysis given all correlation is low [duplicate]

A question on approaching regression analysis when all Y - X correlation is low; almost all |correlation| < 0.1 To give an outline of data I have: Y (Store sales by month); n>2000 Xi (Macro-...
Jun's user avatar
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Choosing between Negative Binomial, Zero-Truncated NB, and NB with Arithmetically Altered Outcome (SAS)

I am modeling longitudinal Days of Pill Supply with predictors Number of Rx's and Patient Race. I was not able to use linear regression (proc reg or proc glm) because of heteroscedastic residuals, so ...
L.S.'s user avatar
  • 161
4 votes
2 answers
40 views

Choosing the right modeling procedure

I am working with a dataset (electronic medical record extract) and trying to find out whether there is a difference in a continuous integer outcome (RxTotal, mean=7.4, range 2-34, skew=1.6, kurtosis=...
L.S.'s user avatar
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3 votes
0 answers
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Can a Gaussian Process predict random events?

I know that we can use Gaussian processes effectively for function approximation and regression. However,suppose there is a sequence of points in time $S = \{s_1, s_2, \dots, s_n\}$, where $s_i$ can ...
Hassan Ali's user avatar
4 votes
1 answer
422 views

Model assumptions - not worth the effort?

This question was inspired by this discussion I read recently. After obtaining our results, the assumptions from the models we used should be checked, otherwise these results may be deceiving. ...
JED HK's user avatar
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1 answer
34 views

The Concept of Mixed-Effect Modeling in Gardening

I have random factors such as Flower, Allotment and Gardener. Gardeners scored the flowers. Flower Crossed in Allotment. Flower Nested in Gardener, and Allotment Nested in Gardner. Can I analyse each ...
user330's user avatar
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3 votes
1 answer
73 views

Probability distribution for weights in Gym machine?

Below is the image of weights in Gym, I would like to know what probability distribution that would fit the wear and tear of the weights. Below are my initial thoughts: (1) Has to be discrete ...
forecaster's user avatar
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Could the community provide critiques on my method for picking features for modeling?

I just started a new job that is a bit more stats heavy than my old DS job. In my old gig I was mainly in the domain of scraping, descriptive statistics, visualizations, dashboards, etc. So I'm having ...
Nye307's user avatar
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0 answers
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Commodity Price Modeling with Time Series vs. Return

TLDR: Assuming that the current commodity prices are influenced by a variety of factors, including the prices from the previous period. Given this context, should I explore the relationship between ...
Aaron's user avatar
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3 votes
1 answer
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mixed effects model when within group variance cannot be estimated

What is a mixed effects model when the within group variance cannot be estimated. For example I have an outcome that is very rare to begin with. Less than 5% of children have this outcome. Then I have ...
Sundown Brownbear's user avatar
3 votes
3 answers
71 views

proper test for indifference of two groups

I'm reaching out with a question that, at first glance, might seem elementary, but given some perplexing advice from my thesis supervisor, I find myself in need of your expertise. The scenario is ...
Wu Jilong's user avatar
0 votes
0 answers
8 views

panel causality relationship in long run and short run

What econometrics should I use when I want to estimate the causality relationship between variables in long-run and short-run for panel data? Whether models such as panel VAR, panel VECM or panel ADRL ...
Huy Lê Thanh's user avatar
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0 answers
30 views

Unifying predictions from the same model but with differing assumptions

I'm working with the same dataset and I'm exploring several approaches to modelize it. Each model applies the same model but operates under different assumptions, such as: Stationarity vs. Non-...
Anewone's user avatar
3 votes
1 answer
30 views

Modeling quesion, linear regression or survival analysis

I am analyzing a dataset where the outcome variable is "teenagers' recreational drug use in weeks." This is continuous and highly skewed outcome variable. While the range spans from 2 weeks ...
Sundown Brownbear's user avatar
4 votes
1 answer
553 views

Statistical power of my study

I am writing a paper for a journal. I have been asked to calculate the statistical power of my study. I have zero idea about how to do that. I am an engineer and never cared about this kind of ...
GGChe's user avatar
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0 answers
16 views

What is the reason why creating induced subgraphs based on anatomical definitions doesn't seem to be a popular analytical technique?

I was having a discussion with some colleagues about graph theory and how it could be applied to analyzing fMRI datasets, where the matrix is a pairwise correlation matrix between pairs of region of ...
Syuma's user avatar
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1 vote
0 answers
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Is using aggregated usage data more efficient than using flattened usage data to build a ML model in anomaly detection? [closed]

We're tracking users' hourly usage on our cloud service and have a risk model that uses aggregated usage data plus other signals to identify potential fraudsters. Basically, it's an anomaly detection ...
Jiayu Zhang's user avatar
2 votes
1 answer
41 views

Is It valid to use a Linear Mixed effect Model to quantify a group 'summary' value and plot it when the factors are all categorical?

I currently have a dataset with two factors: Gene and Timepoint. Both of these factors are categorical in nature where Gene has 2 levels defined as control vs disease, and timepoint has 4 levels: ...
Syuma's user avatar
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0 votes
0 answers
23 views

Negative Variance LS Estimator

I am estimating moisture utilizing measurements from a thermal imaging camera. For context, my implementation becomes a FIR filter, and is very similar to the Weiner Filter. I am using several pixels ...
Johan's user avatar
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1 vote
1 answer
82 views

logistic regression vs poisson rate regression

I have some confusion about logistic regression, Poisson regression and Poisson rate regression and I hoping to get some answers that can clear the cobwebs in my mind regarding this confusion. My ...
Sundown Brownbear's user avatar
0 votes
0 answers
40 views

On choosing statistical test to see the effect of 2 types of essential oils on e.coli

So I'm trying to see the effect of 2 different types of essential oils on e.coli (Grade 12 student - this is for my IB Biology EE) What I did was that I increased the concentrations of the oils from ...
anonymous1924's user avatar
0 votes
1 answer
37 views

non-significant p value in a multivariable cox regression following exhaustive model selection

I run an exhaustive model selection for Cox proportional hazard in R using "glmulti" package. I used the best model for creating multivariable Cox regression. In the multivariable Cox hazard,...
Ahmed Elkoumi's user avatar
5 votes
1 answer
246 views

Exponential likelihood

I have a random variable $T$ that represents time to failure. I can make a simple model where $T$ is exponentially distributed iid for some rate $\lambda$. We can estimate $\lambda$ with e.g. failure ...
monochrome's user avatar
0 votes
0 answers
29 views

How to interpret the coefficients of a logistic regression on a proportion?

Further to my previous post , it seems that one can/should use a logistic regression to model a proportion. How do I interpret the coefficients of a logistic regression when the outcome variable is a ...
CyG's user avatar
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1 vote
0 answers
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Why do we require a final evaluation in k-fold cross validation?

I am aware that there are many answers to many posts on this topic (see: 1,2, 3). Generally, the common answer is that this is 'best practice', it avoids 'data leakage' or overfitting. Is there a ...
CyG's user avatar
  • 191
2 votes
1 answer
64 views

Analysis of Alzheimer data

I have two data sets with values from Alzheimer's and healthy patients. My task is to find a decision rule for evaluating the patients. The task in the original wording: "Think of a decision rule ...
aren's user avatar
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1 vote
0 answers
11 views

Help finding Bayesian model with multi-modal posterior [closed]

Background: There is a paper (link) that concerns combining MCMC methods with a normalizing flow (a type of generative model). The basic idea is that the normalizing flow helps propose samples, which ...
caitlin's user avatar
  • 31
5 votes
1 answer
74 views

approches for linear extrapolation of xgboost model tails

I would like some insight on known approaches for linear extrapolation on tails of xgboost models. The current model is missing data at the distribution tails and is thus predicting flat trends for ...
aort01's user avatar
  • 151
2 votes
0 answers
18 views

Logistic Regression Pattern in Deviance Variance Across Variables

I fitted a Logistic Regression model for a Customer Churn dataset with the following results I tested this model with a validation set and calculated the ROC AUC score, which was approximately 0.85 – ...
lucas17's user avatar
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0 votes
0 answers
17 views

Distribution of Outcomes From Many Independent Events With Varied Associated Probabilities

I have a problem in which I need to visualize the distribution of possible outcomes from a large number of independent Bernoulli events with varying probabilities among those events in python (summing ...
SemiActive's user avatar
0 votes
0 answers
56 views

Impact of between-group differences in the independent variable on between-group differences in the dependent variable in a known model situation

I'm grappling with a specific question: I have two independent groups and a known function f = x ⋅ y ⋅ a + z, where x, y, and z are variables and a is a constant (the same for every participant in ...
Sloughon's user avatar
0 votes
1 answer
31 views

How to Handle Infinite Values in Feature Engineering for Machine Learning Models

I'm currently working on a machine learning project where I am creating new features related to the ratio of bytes sent and received in a communications network. However, I'm facing a challenge: when ...
Camilo Piñón's user avatar
0 votes
0 answers
38 views

How to get an hourly forecast from mean, max forecast and historicals

I have hourly historical temperature curve for a month say January. I also have a monthly peak and a monthly mean forecast for March 2024 (two values). Using this - How can we get an hourly forecast ...
Vineet's user avatar
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0 votes
1 answer
71 views

What studied statistical model (if any) fits this application?

I'm having trouble identifying what statistical model or methodology is suited for my application. My situation is as follows: I want to create a stock trading agent that trades a single stock-cash ...
QMath's user avatar
  • 419
1 vote
0 answers
36 views

Valid forms of exploratory data analysis for time series that don't assume stationarity?

Lets say we are given a time series sample and want to try to create a model to forecast future values of said time series When trying to build a model to forecast time series data, many statistics ...
QMath's user avatar
  • 419
0 votes
1 answer
30 views

Binomial random effects model with disaggregated covariates

I have an numerator and denominator data for an outcome variable from multiple countries disaggregated by several factors, such as age and gender - similar to: country gender age denominator ...
jpsmith's user avatar
  • 329
0 votes
0 answers
21 views

Can we interpret the probability of fails the same way than the probability of success in a binomial model?

I have used the data "Chickweight" in R to make a dummy example model ...
lframond's user avatar
  • 111
4 votes
2 answers
104 views

How to check linearity of a variable without plots/graphs in R?

I'm running a longitudinal study comparing patients with a lung growth which either developed into cancer (cancer_status = 1) or didn't (= 0). Here is some example randomly-generated data in the same ...
bmr's user avatar
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1 vote
1 answer
71 views

How to model this dataset?

I'm working with a dataset (my_dataset) that comprises six groups of individuals (Team_ID) with a dependent variable ...
Barbab's user avatar
  • 333
1 vote
2 answers
590 views

Support Vector Regression vs. Linear Regression

I am new to ML and I am learning the different algorithms one can use to perform regression. Keep in mind that I have a strong mathematical background, but I am new in the ML field. So I understand ...
kubo's user avatar
  • 145
1 vote
1 answer
70 views

How can Null model likelihood be higher than Fitted model likelihood

As far as I know, when fitting a GLM, the fitted model should always have a higher likelihood compared to the null model (with only an intercept) for the same training set. When I run a small ...
Kozolovska's user avatar
  • 1,355
5 votes
1 answer
65 views

With logistic regression, how does one choose a number of predictors when preregistering a study?

Harrell's Regression Modelling Strategies suggests that the number of predictors should not exceed $m/10$, $m/15$ or $m/20$.* For logistic regression $m$ is $\textrm{min}(n_1, n_2)$, where $n_1$ and $...
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