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
0
votes
0answers
8 views

Lagged (in)dependent variables: 2 time periods, Panel Model vs. OLS

Summary I have a dataset with observations regarding an industrial process in two time periods. My goal is to find predictors of future performance, and I am wondering whether panel data regressions ...
1
vote
1answer
20 views

Sample stratification by dependent variable in linear regression analysis

I have a theoretical question that I would like some guidance on. Is it ok to stratify a sample population by the dependent variable? Does this bias regression results? For example, I'm doing an ...
0
votes
0answers
13 views

questions about different ways to define a rate (such as fertility rate) as a dependent variable in a regression

Lets say I want to run a regression of fertility on some independent variables at the county level. There are a couple options of how to do this, one would be to just create the fertility rate by ...
0
votes
0answers
10 views

Comparing two approaches to modeling dependence in bi-variate Gaussian regression

Presume we would like to model the dynamics of two related variables as a bi-variate Normal, while also accounting for the effect of other covariates (via regression). E.g. I would like to model ...
0
votes
1answer
51 views

Can I build a statistical model for a dependent variable based on other dependent variables?

I have a question about statistical models. In particular, whether it is correct/meaningful to build a statistical prediction for a response variable based on the other dependent variables from the ...
0
votes
0answers
23 views

Which method of analysis to use on SPSS for two dependent variables (likert scale) with repeated measures?

I am conducting research for my master's thesis regarding the phenomenon of Hindsight Bias. I have four experimental conditions in which the DVs include foreseeability and inevitability, and they are ...
0
votes
0answers
6 views

Composite outcomes

I am quite new and not an expert in statistics. I am just wondering what is the best way to assess differences between treatment arms in a trial in the primary composite outcome including all events ...
0
votes
0answers
15 views

Dependent variable count or continuous?

If my dependent variable is " How many hours do you drive per day"... and respondents have answers in positive integer numbers like(10 hours, 12 hours), will it be considered count data or continuous ...
1
vote
1answer
37 views

Using a logistic regression on censored data

I am interested in modeling the probability of default (PD) of a loan product. Data I have a dataset going back several years. Most of the loans have reached their terminal state (paid off or ...
1
vote
0answers
20 views

If the dependent and independent variables are not stationary, but they are first difference stationary. Can I use the original variable?

If the dependent and independent variables are not stationary, but they are the first difference stationary. Can I use the original variable?. If I use the percentage change for the dependent and ...
0
votes
0answers
17 views

Conditionally Dependent Variables

I'm curious, since I do not know the name to this phenomenon, how do we handle variables that are conditionally dependent in the following sense. E.g in case of bank. Relationship: A checking ...
5
votes
3answers
95 views

Are dependent variables necessarily functions of one another?

The problem Suppose you have two variables $X_1,X_2$ so that $X_1\not\perp\!\!\!\!\! \perp X_2$. Do we necessarily have that a functional relationship exists between them? I am assuming random ...
0
votes
0answers
18 views

How to Handle Conditionally Dependent Variable

Correct me if I am wrong, but from what I've been reading for Machine Learning models, it is the procedure to find independent input features that are correlated to your target variable. However, ...
2
votes
1answer
35 views

A question about characteristic functions

A probability 101 question. We know that if two variables $X$ and $Y$ are independent then the characteristic function $\phi_{X+Y}(u)$ can be written as \begin{equation} \phi_{X+Y}(u)=\phi_{X}(u)\phi_{...
17
votes
1answer
508 views

Predicting y from log y as the dependent variable

In the book Introductory Econometrics by Wooldridge the chapter, which deals with predicting values of $\hat{y}$ (chapter 6.4 in the 5th edition) states the following: If the estimated model is: ...
0
votes
0answers
18 views

multivariate analysis with mixed numerical and categorical dependent variables

I have one independent variable (yes/No) and several covariates (sex/age and so on..), five dependent variables (four continuous, normal distributed and one categorical as yes/no). I want to look up ...
1
vote
0answers
16 views

Array size as a random variable in graphical models

Assume that I want to model a mixture of sentences. There are two different sources generating sentences with specific sentence length and word distribution. I had came up with the following graphical ...
0
votes
0answers
12 views

Coding of response variable avoiding dichotomization

Frank Harrell and many others say - dichotomization should be avoided for the power maximization, it can easily be checked using simulations: Wilcoxon test is more efficient than any other form of ...
2
votes
0answers
31 views

Why does adding a dependent variable to a MANOVA remove significance?

We designed an experiment with 2 discrete independent variables (IV), 1 (measured) confounding variable, and 2 dependent variables (DV). We hypothesize that the two IVs interact on both DVs. Right ...
0
votes
0answers
16 views

How related are the categories of a categorical dependent variable

There is a set of numerical and categorical independent variables and one dependent variable that is categorical. Some of the categories are far to be related with the rest, but most of them are very ...
0
votes
0answers
26 views

Is there a maximum amount of dependent variables for MANOVA?

I have a dataset where the influence of 3 manipulations (vs placebo) is tested on 17 different outcome measurements. To avoid having to run 3*17 = 51 ANOVAs to see which type of manipulation has an ...
0
votes
0answers
12 views

Predict with average values of dependent features

I created linear regression model to predict story points by individual team member (in sprint). Since story points are relative by sprint team, I trained my model after scaling story points to 0 - 1 ...
1
vote
1answer
23 views

Which statistical test should I use for testing dependent variables across 5 datasets?

5 pupils are given the task of hand drawing a hundred trapezoids with a given perimeter. The vertices are marked A,B,C,D counter-clockwise starting with the longer parallel edge (A and B). The lengths ...
0
votes
0answers
48 views

Cross-classified multilevel model with lagged dependent variable Using R

I am a bit stuck with my model and I wonder if this is even possible using R. Basically I want to use a lagged dependent variable (LDV) in a cross-classified multilevel model (MLM). Following remarks ...
0
votes
1answer
40 views

Test for the influence of a manipulation on multiple dependent measurements (order effects, multiple comparisons)

I have a dataset which looks like this: ...
0
votes
1answer
67 views

Quantitatively assess if independent variables are sufficient to determine dependent variable behaviour

I have the matrix of the independent variables X with dimensions n_samples x m_features and a vector ...
0
votes
1answer
21 views

Measuring mutual dependencies between variables. The most fundamental relation

One has a simple dataset of 3 independent variables, e.g., x, y, z. Now: y and z are logically connected (this is known a priori) and indeed a nice & tight correlation (small scatter) between ...
2
votes
2answers
457 views

Independent and dependent variables Machine Learning

I want to start a regression model on lottery numbers, my database consist of the dates, and results(numbers). In order to do a regression model I believe you need independent and dependent variables, ...
0
votes
0answers
78 views

multiple imputation for k-means clustering + outcome variables

I’m exploring whether distinct clusters can be derived from real-time, smartphone logs of daily social behaviors, and how these clusters predict self-reported depression and loneliness. My plan is to ...
0
votes
0answers
17 views

Have $(U,V)$ be a pair of Bivariate Gaussian variables with mean $0$, variance $1$ and $Cov(U,V) = p$ where 0 < ρ < 1 [duplicate]

Have $(U,V)$ be a pair of Bivariate Gaussian variables with mean $0$, variance $1$ and $Cov(U,V) = ρ$ where $0 < ρ < 1$ I'd like help finding the density of $U+V$ So far I have tried to use $...
0
votes
0answers
52 views

What do these SAS plots imply about the regression outcomes?

I have run a Tobit regression, and in the output the following charts are generated (at the end of parameter estimates). I cannot relate these charts with the parameter estimates. Could someone give ...
0
votes
0answers
31 views

Predicting elections: Probability distribution from betting odds and dependence

Suppose I want to find the percentage of votes each party will get in elections. I have following odds from betting companies. My first thought is to find the probability for each party achieving a ...
2
votes
1answer
49 views

Decomposing a random variable into marginals and copula

I’m having trouble getting understanding how to actual construct a copula, from my understanding it captures the purely joint features of a joint distribution. I’ve been working with the following ...
0
votes
0answers
30 views

Signal Detection Theory: correct rejections - what underlying processes?

Suppose we have a word recognition task, on the basis of which we compute the four rates defined in Signal Detection Theory as Hits, False Alarms, Correct Rejections, and Misses (HR, FAR, CRR, MR). ...
0
votes
0answers
8 views

Finding dependence of output variables on input variables

I want to perform a regression using neural networks. My input has 5 parameters [a, b, c, d, e] and the output is 4 variables [x, y, z, w]. Total number of observations I have is 1000. I wanted to ...
1
vote
2answers
53 views

What is the difference between having input parameters that are independent/dependent in ML tasks?

This is more of a general question. But, when you feed in inputs into a machine learning algorithm, are the inputs typically dependent or dependent? What are the implications if the inputs are ...
1
vote
0answers
18 views

Interesting and unusual dependent variable--how do you think it should be handled?

We have 2 dependent measures, which are both distributed from -4 to +4 in discrete steps. This is because the values are based on people's responses to four questions about whether they spend more ...
2
votes
1answer
20 views

Interesting variant on discrete probabilistic problem

Suppose $X \sim U(0,1)$ and $Y$ and $Z$ are random variables that depend on $X$. I've solved a problem where $Y$ and $Z$ are discrete (binary) and so finding the joint pmf just amounts to calculating ...
0
votes
2answers
66 views

SPSS Paired Samples T-Test outcome interpretation

Hypothesis: -Blood pressure will decrease after intervention Results (blood pressure): Systolic bp before mean: 102.00 Systolic bp after mean: 97.10 Diastolic bp before mean: 70.80 ...
1
vote
0answers
44 views

Sum of two dependent random variables with copula

I'm trying to calculate sum of 2 random variables by using Copula Theory in R or Matlab. However, I have very limited knowledge about probability. Actually I read a lot of theoretical information ...
1
vote
0answers
66 views

Within-person centering the outcome variable?

What do you think of within-person centering the outcome variable? If my research questions is clearly about within-person effects (in a longitudinal multilevel model), can I just use the centered ...
0
votes
1answer
72 views

Using predicted probabilities from logistic regression as dependent variable in a linear regression

I'm trying to run a Response Surface Analysis in SAS, but this is only possible with a continuous outcome, whereas my outcome variable is binary. I got the advice to first run a logistic regression ...
1
vote
1answer
38 views

Can a linear and logit model have the same shape?

While I was working on an exercise based this book, I discovered something interesting. When I fit a logit and simple linear probability model on the data (see code below), the predictions are almost ...
1
vote
0answers
76 views

Mixed Effects Models: Does Null Model Intercept Variance Set the Limit on Proportion of Dependent Variable Explainable by Full Mixed Effects Model? [closed]

I have a random intercept and random slope mixed linear model with a continuous dependent variable. To calculate ICC, proportion of dependent variable explained by model with predictors at Level-2 and ...
1
vote
2answers
709 views

Confounding variables in experimental study

We conducted a study to analyse the effect of tablet named 'xab' that help smokers to stop smoking. 5500 of smokers are selected. half of them were given different doses of tablet while the other ...
0
votes
2answers
435 views

Will Chi Square Test work for high number of categories?

I have a dataset of 1000+ records. In this dataset, I have two categorical features, Ticket-Label and Survived. Ticket-Label has 54 unique categories and Survived has 2 categories. The chi square test ...
0
votes
1answer
40 views

differences between conditional probability and dependency

Sometimes, I read articles about conditional probabilities and other articles about conditional dependency. My question what is the main differences between them? For example, "https://en.wikipedia....
0
votes
1answer
24 views

Analysing partially ordered responses

I'd like to analyse judges' decisions on bail. Ie some decisions (remand in prison) and clearly worse than others (unconditional bail). But in the middle there are a range of possible responses that ...
3
votes
3answers
160 views

Linear model for positive response variables

Very concise question: if I model a phenomenon which takes only positive values (for example, revenues or production) using the classical OLS, what are the consequences in terms of bias, efficiency ...
0
votes
0answers
116 views

How to use Correlation of variables to predict future pattern

I have data set of file generating from some user. User can generate 1, 2, 3,4, 5 and more files during a day. Data set example: Day one - 2 files generated - first is at 09:10 and second one at 10:...