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
1
vote
0answers
15 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
14 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
16 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
5 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
11 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
36 views
0
votes
1answer
56 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
15 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 ...
1
vote
1answer
90 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
15 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
14 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
47 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
18 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
40 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
25 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
4 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
35 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
19 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
28 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
31 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
29 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
41 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
36 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 ...
0
votes
0answers
12 views

Multiple comparisons, should I run a one-way multivariate analysis or can I use Mann Whitney?

I am analysing some study data and am unsure the appropriate statistical test to use. The study involves watching a film. 50% of participants saw version 1, 50% saw version 2 - (the difference in ...
0
votes
0answers
21 views

Can I do multiple ANOVAs without correcting for multiple comparisons?

In my study I have one repeated measures factor that I manipulated on two levels and one between-subjects factor that I manipulated on 3 levels (three groups), resulting in a 2x3 design. I also have ...
0
votes
0answers
23 views

Can standardized variable be used to generalize sample results to whole population?

I have a dependent variable(wage), and two variables, that are correlated to wage (country and ...
1
vote
0answers
56 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
630 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
70 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
32 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 ...
0
votes
0answers
24 views

how to test for sufficient variations in the dependent variable [panel]

I am planning to perform a panel analysis with the sample size of 1020 individuals that have been assessed through their career ages. The panel is unbalanced (missing observations). My dependent ...
0
votes
0answers
23 views

Comparing the mean of predicted values for a misspecified model against the mean of the observed values

I have a regression that I have run on average ratings for some products (dependent variable) and their characteristics (Model 1). I have reason to believe there is a prejudice against a specific set ...
3
votes
3answers
89 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
110 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:...
0
votes
1answer
158 views

Diff-in-diff with mactched control group

I want to run a diff-in-diff model. To choose an appropriate control group, I use a nearest-neighbor matching model based on several determinants of the outcome variable that I study. I was ...
1
vote
1answer
255 views

Dealing with non-stationarity in panel data

I am using panel data for my analysis. My dependent variable is non-stationary while all my explanatory variables are stationary. Also, my dependent variable is a bounded variable (an index variable ...
0
votes
0answers
12 views

synthetic datasets without any dependecies between features

I have to create a synthetic data set without any dependencies between features so that this equation should be hold. I thought about to take simply several Gaussians or randomisers, each would be ...
0
votes
0answers
24 views

Random variable concept and terminology [duplicate]

I am a programmer with little mathematical background who started to study statistics/ML recently. I quickly stumbled upon the random variable term and it was hard for me to understand why in ...
0
votes
3answers
208 views

Dependent variables - BMI and Weight [closed]

I have to figure out, which of the two variables (BMI and Weight) is the dependent. So I can make a scatterplot. Can you please tell me which one? And why? I tried searching the internet, but without ...
0
votes
1answer
35 views

Does taking logs to supress hetroskedasticity only work for the dependent variable?

I have been told that by logging variables in a regression that hetroskedasticity of errors can be reduced. Is this the case also if only my dependent variable is logged?
0
votes
1answer
341 views

Odds ratio for continuous dependent variable by regression analysis

Can the odds ratio be calculated for a continuous dependent variable using logistic regression? If yes, kindly explain the procedure in SPSS. Further, can we apply logistic regression to an dependent ...
45
votes
3answers
3k views

Where does the misconception that Y must be normally distributed come from?

Seemingly reputable sources claim that the dependent variable must be normally distributed: Model assumptions: $Y$ is normally distributed, errors are normally distributed, $e_i \sim N(0,\sigma^2)...
3
votes
2answers
138 views

Can I do regression without dependent variable?

I have a dataset of auto thefts that has the date, day, time the thefts occurred on. My independent variables would be day of the week, month, hour of the day, etc. I want to see if auto thefts is ...
1
vote
0answers
398 views

Is there any value in correlating a binary dependent variable and categorical independent variables?

I'm constructing a logit model with a binary dependent variable (probability of exiting unemployment). On the right hand side (independent variables), I have a few continuous variables and a number of ...
1
vote
1answer
209 views

My dependent variable is first difference stationary. Can I use the original variable?

I found my dependent variable is first difference stationary, but does this mean I have to use the first difference as my dependent variable? Or can I use my original variable as my dependent? My ...
0
votes
0answers
36 views

The law of large numbers mediates predictor-outcome relation, what to do?

I am conducting a random forest analysis in which a predictor is naturally correlated to the outcome. That is, the predictor is the amount of sunlight a patient received during his admission in a ...
0
votes
2answers
261 views

Dealing with probable outliers in the dependent variable

I am trying to fit a simple regression to a data set with ~45,000 observations. The dependent variable is revenue growth, but I'm concerned some observed values are incorrectly entered data. To ...