Skip to main content

Questions tagged [dependent-variable]

In a regression model, the dependent variable is modeled as a function of other variables (regressors). Other common names are 'response', 'outcome', 'predicted variable', 'criterion', 'target', etc.

Filter by
Sorted by
Tagged with
2 votes
1 answer
73 views

What are the `estimates` returned by `avg_slopes()` in modelsummary?

I have an interpretation question of R's marginaleffects avg_slopes function for logistic regression models. Consider the ...
spindoctor's user avatar
0 votes
0 answers
24 views

Difference in means and variances of dependent samples

I am performing a simulation study where different values of an exposure X are repeatedly assigned to the same individual (200x in a sample of >10000 people). The way that assignment is done is ...
JuM24's user avatar
  • 21
0 votes
0 answers
29 views

Multiple Dependent Variables, One Independent - with dummy variables

I am trying to run regression models and don't know what type of regression to be running. I have one independent variable (binary variable) and 8 dependent variables (3 discrete, 3 categorical, 2 ...
Margot's user avatar
  • 1
2 votes
1 answer
27 views

impact of time to particular event on response

I am trying to evaluate which variables have the impact on the outcome. My clinical team wants to check if time to particular event has an impact on the outcome. If particular event occured, then time ...
Kate's user avatar
  • 185
15 votes
1 answer
480 views

What distribution should I use to predict three possible outcomes

I am 70, left school at 14 but took to maths a few years back to ward off dementia so please excuse the naivety of my question. I have been using Poisson distribution to solve my problem but I dont ...
Simon Bates's user avatar
0 votes
0 answers
48 views

What is dependency on sequential data?

We know that Whenever the points in the dataset are dependent on the other points in the dataset the data is said to be Sequential data. A common example of this is a Timeseries such as a weather data....
D. S.'s user avatar
  • 69
0 votes
0 answers
21 views

Addressing Scaling Bias in Panel Data Analysis

I am running an (unbalanced) panel data analysis, where the dependent variable is, $fixed\ cost\ (per\ ha)$ for an agricultural firm $i$ in period $t$. The explanatory variables are the hectares per ...
Tom's user avatar
  • 528
0 votes
0 answers
17 views

Target encoding in linear regression

I have a dataset with the loss rates of each contract as dependent variable. As independent variables I have country (four values), profession (5 values) and income (continous variable). I apply ...
Vit123's user avatar
  • 1
1 vote
2 answers
31 views

PSPP multiple variable linear regression analysis

I'm just starting with linear regression, and I'm having trouble understanding it. It doesn't seem to make any sense to me. Yes, this is school work, but instead of asking for direct answers, I need ...
Juster's user avatar
  • 111
0 votes
0 answers
18 views

Interpreting Lagged Dependent Variable in Binary Logistic Regression

I am running a binary logistic regression to test the purchasing of a gym membership in 2021 against a series of controls (ie. income, gender). Included amongst these control is a lagged dependent ...
Vito's user avatar
  • 123
1 vote
1 answer
48 views

Negative percentages as dependent variable

I am analysing the effects of legal origin on the performance of firms within Canada and Quebec, and I'm in the process of gathering and cleaning the panel data as I was hoping to conduct both entity ...
stew21's user avatar
  • 11
3 votes
1 answer
58 views

Calculating binomial distribution probability for dependent trials

Context: I am a software developer and recently we've had a bug report saying that one of our login systems are potentially insecure to a brute-force attack. I need to come up with a formula to ...
choket's user avatar
  • 33
0 votes
1 answer
27 views

Predicting binary outcome when predictor variable increases

Suppose I have a simple dataset of numerous observations, each with a continuous numerical variable $x$ and a binary numerical variable $y$ (with values 0 for unsatisfactory, 1 for satisfactory). How ...
ezrarusk's user avatar
0 votes
0 answers
26 views

Is there a way to calculate lambda for a Box-Cox transformation when there are two categorical independent variables in R?

I have the following model where X is the duration of a particular event, A is a factor with five levels and B is a factor with two levels. I want to run a type III ANOVA analysis. ...
Insect_biologist's user avatar
1 vote
0 answers
65 views

ValidError, invalid input, x is constant

how shall I investigate the data and preprocess? I'm trying to do a heatmap analysis of cointegrated pairs using pvalues. Perform cointegrated pairs analysis cointegrated_pairs = [] correlation_matrix ...
Wynton Lam's user avatar
0 votes
0 answers
55 views

Probability of a certain final score in soccer when you know each of the two teams' probabilities to score a certain number of goals

Let's suppose that you have data from about $2000$ soccer matches from a certain league. Your data shows that the home team's probability of scoring $0$ goals is $0.245263157894737$. The away team's ...
Giorgos Papatheodorou's user avatar
0 votes
1 answer
101 views

How are the joint distribution and dependency related? [closed]

Here are some notes about copula functions, Copula is a probability model that represents a multivariate uniform distribution, which examines the association or dependence between many variables. Put ...
Etemon's user avatar
  • 121
0 votes
0 answers
11 views

Removing observations with missing target values in the test set

I'm building my first predictive model and seem to be having a fundamental confusion about missing target values. I'm predicting treatment outcome (with both regression and classification methods for ...
olke's user avatar
  • 115
0 votes
0 answers
13 views

Can a Dependent Sample T-Test be Used on Sample Group (A) of 100 Electrical Devices, Tested at time, t1, shuffled, and Tested at time, t1?

Description: I have a group of 100 electrical parts being testing for Forward Voltage, at time, t_1. This is my sample group, S1. This same group is undergoing a stress test that may or may not affect ...
randomguyz's user avatar
4 votes
1 answer
164 views

Can I use logistic regression if one category of the dependent variable has a very low frequency?

An example of 100 subjects. Let's say I wish to study the impact of literacy levels (0 as limited and 1 as adequate), anxiety levels (0 as no anxiety and 1 as severe anxiety) and sex (0 for female and ...
An116's user avatar
  • 367
13 votes
5 answers
2k views

If Cov(X,Y)=Var(Y), what is the dependence between X and Y?

In a problem I have found that $$Cov(X,Y)=Var(Y),$$ where $X$ and $Y$ are random variables. What can I conclude on the linear dependence between $X$ and $Y$? Thank you!
Jo R's user avatar
  • 331
2 votes
2 answers
161 views

Building a predictive model for the Return on Investment (RoI)

I am working at a company that invests in ads for apps at different stores. I have a dataset containing the columns date, app, <...
Alberto Perez Martinez's user avatar
1 vote
1 answer
74 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
0 answers
39 views

Are precipitation and soil moisture time-independent variables?

I was studying about Copula functions from here. It says: Basically, copula is a set of mathematical tools that have the ability to connect two or more time-independent variables (Nelsen, $2003$) As ...
Etemon's user avatar
  • 121
1 vote
1 answer
34 views

Target variable is defined by combination of input features

I am trying to create a classification model which predicts whether or not a customer comes back to make a second transaction (after having made an initial transaction). I have details on date of ...
piper180's user avatar
  • 153
1 vote
0 answers
99 views

Is it possible to apply a Kruskal-Wallis to data without clear dependent/independent variables? [closed]

I'm trying to find a NHST for my data that, as far as I know, are only compatible with a Kruskal-Wallis test. However, my variables aren't really identifiable as either dependent or independent; ...
koloeus's user avatar
  • 29
0 votes
1 answer
63 views

Effect of two independent variables on a dependent variable, each containing several factors in Likert scale form

For example, the first independent variable consists of 30 factors, the second independent variable consists of 21 factors, and the dependent variable consists of 21 factors. There are four options ...
wawar's user avatar
  • 1
0 votes
1 answer
66 views

Experimental design study on arousal/attention

I hope this question is simple enough, suits this forum and does not consume much of your time. Essentially, want to make sure I have the appropriate design that answers my research question without ...
Jose Teles's user avatar
1 vote
1 answer
67 views

Scatterplot relationship between dependent and independent variable for linear regression analysis

I am performing an univariate linear regression analysis. Before running the model I was always told to get an idea of the relationship between the independent and dependent variable through a ...
fredi96's user avatar
  • 45
0 votes
1 answer
30 views

Combining location based probabilities from GPS data

I'm working with GPS data and have billions of GPS points stored in a DB. I'd like to be able to use this to create a class likelihood function that I can use somewhere else as as a visualisation or ...
RedM's user avatar
  • 111
5 votes
5 answers
461 views

Structural Equation Model design

Is it necessary in structural equation modeling (SEM) to incorporate all potential independent variables that could affect the dependent variable? Or is it acceptable to examine the influence of only ...
Marjaan's user avatar
  • 51
0 votes
1 answer
26 views

Normalised versus true racing times as DV for a learning experiment?

I have a question about using ratios as variables in alpine ski racing research. We want to compare skiers' performance on different days, but snow conditions affect the results. To address this, we ...
Cmagelssen's user avatar
1 vote
2 answers
123 views

(Multivariate) normality assumption for dependent variable

In their book on multilevel analysis Hox et al. (2017) write in chapter 13: 'The main assumptions are [...] (multivariate) normality for dependent variables, which is the focus of the current chapter.'...
Ben's user avatar
  • 23
0 votes
0 answers
31 views

Cox regression with binary time-varying covariate

I am researching the association between menopause and the incidence of diabetes(outcome). I have a baseline and three follow-up assessments. Given that women transition from non-menopausal to ...
Noushin's user avatar
0 votes
0 answers
7 views

Anyway to transform data with a varying derivative into something that can give me comparative percent changes everywhere?

Sorry about the confusing title, I am so confused that I don't even know how to frame the question. I have a device that gives me two sets of output values depending on how I set the surface charge of ...
Dominik Duleba's user avatar
0 votes
0 answers
120 views

How to encode multiclass target variable?

I have a ML project for classifying news articles. In my dataset I have a target variable called "category", which represents type of the article, ("IT", "Science & Tech&...
CraZyCoDer's user avatar
0 votes
0 answers
14 views

Binary response mode with non-binary response variable [duplicate]

I’m a bit stuck with what seems like a simple question. I have data from an experiment whereby participants had to provide ‘yes’ or ‘no’ answers (so the response mode was binary). Their scores, ...
Amelia's user avatar
  • 1
1 vote
1 answer
198 views

Understanding the Difference Between Independent and Dependent Variables

I'm new to statistics and I'm struggling to grasp the distinction between an independent and a dependent variable. For instance, if I want to examine the correlation between daily COVID-related deaths ...
Diana Mele's user avatar
1 vote
1 answer
15 views

Can I apply a time dependant covariate to a cox regression with calendar-based time scale using data with staggered entry

I have a retrospective study evaluating the effectiveness of an intervention in reducing COVID infections on subgroup of patients. Using a control and intervention group, I was hoping to set a time-...
carl's user avatar
  • 11
1 vote
0 answers
151 views

Implementing bias-adjustion for step3 latent profile analysis in R [closed]

I am identifying a latent profile model with the Mclust package in R. After identifying an optimal number of cluster I would like to identify possible covariates and distal outcomes via logistic/...
David Janda's user avatar
1 vote
1 answer
29 views

Coefficients stayed the same after re-levelling MLR variables

I have an MLR model created in R, regresses the dependent variable y, against the following explanatory variables: age (numerical), hair colour and eye colour (...
sym246's user avatar
  • 487
1 vote
0 answers
18 views

What is the independent value in an roc curve?

An ROC curve is plotted with (1-False Positive Rate) on the X-axis and the True Positive Rate on the Y-axis. However, the way in which each point of the curve is plotted is by first picking a cut-off ...
str31's user avatar
  • 11
4 votes
1 answer
140 views

Inferences about $\mu$ based on the sum of two dependent normal RVs

Given: $X \sim \mathcal{N}(\mu, \sigma^2)$ $Y|X=x \sim \mathcal{N}(0, (\theta x)^2)$ $Z = X + Y$ I want to be able to make hypothesis tests or confidence intervals for $\mu$ using $Z$ and known $\...
be_excellent_to_each_other's user avatar
-1 votes
1 answer
44 views

Dependent variable "controlled" by a binary variable?

in my research the DV should be measured by means of an intent scale (Individual Entrepreneurial Intent Scale). For "controlling" if the answer in DV is correct, I want to include a binary ...
Catalin's user avatar
  • 119
1 vote
0 answers
26 views

Sensitivity analysis based on a dataset with dependent variables

I am part of a company that produces data from satellite images and machine learning/deep learning. We produce different data and sometimes the results of one step will be used as input for the next ...
Victor Allory's user avatar
1 vote
1 answer
73 views

Experiment design - response variable is a sum over a period, low power

I would like to run a statistically rigorous experiment, similar to that of an E-commerce A/B test. I want to create a checkerboard of time periods where I alternate between treatments A and B. ...
wahsmail's user avatar
1 vote
0 answers
40 views

Do you need to normalize labels for models other than neural nets?

As mentioned here, normalizing the target variable often helps a neural network converge faster. Does it help in convergence, or is there otherwise a reason to use it, for any type of model other than ...
bdavidson's user avatar
1 vote
1 answer
143 views

Conditional expectation of dependent variable provided relationship

Suppose I have two random variables, $X$ with PDF $f_X$, and $Y$. Moreover, I know that $Y = h(X)$, and I do know the $h(x)$. Now I want to calculate the conditional expectation of $Y$ given $X$: $$ E[...
Mikhail's user avatar
  • 193
1 vote
1 answer
21 views

Go to models for assessing accurate slope and intercept of model for simluation [closed]

What are your go to models for assessing as ACCURATELY as possible the slope and intercept of given predictor and predicted random variables? The goal is to use simulated predictors + outputted ...
ADAMS zequi's user avatar
0 votes
0 answers
80 views

setting hypothesis based on 2 independent variable

Normally, we have one main IV and other covariates and show relationship with DV. Based on the main IV we conceptualize the research question and hypothesise. Say, Income (IV), Mental Health (DV) plus ...
hanuman's user avatar