Questions tagged [continuous-data]

A random variable $X$ is called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A random variable is continuous if and only if its cumulative probability distribution function is a continuous function.

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Statistical approach to explain variance in different types of soil health data (organic material decomp vs lab based measures)

Seeking feedback and guidance on the statistical approach to explain variance in soil health data for a scientific paper on the sensitivity of organic material (teabag) decomposition to commonly used ...
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Imputing a Continuous P-value Distribution from Discrete P-values

I'm exploring methods to create a continuous-like P-value distribution from discrete P-values. For example, consider the process where a balanced coin is tossed four times per experiment to note the ...
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Impulse response function for discontinous time series

I have monthly time series on forecasts (for the months of August, September, October, November, December, and January.) The data is only available for these months and doesn't exist for other months. ...
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Paired study designs for continuous data vs other types of data

My teacher says : We're going to consider something called a paired design. But for now, we'll only consider this when we're doing continuous outcomes. Sometimes you'll see this in the literature, ...
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Can you derive the standard error of odds ratio, from a method (Kraemer and Kupfer) that derives Risk Difference (and its SE) from continuous data?

Let's say that we have a RCT trial going on and the outcome is a continuous variable. In this paper https://pubmed.ncbi.nlm.nih.gov/23045205/ there are 4 methods that calculate approximated odds ...
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What statistical analysis test can be used to find the direction of effect?

I'm doing research on the effect of strategic video game play on students' mathematical ability. My independent variable is the number of hours spent playing strategic games daily, but my data is not ...
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Two-Group Hypothesis Testing

Will unpaired t-test, definitely reject the null hypothesis if there is a non-zero difference in the population means for the two populations from which the samples are taken?
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Ordinal independent variable (IV) and continuous dependent variable (DV)

My independent variable is measured on a likert scale (1–5). My moderator is dichonomous (yes or no) I want to use SPSS process macro to measure the moderation relationship. Should I use a dependent ...
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Can I ignore "Control" and "Treated" from the output of the mediation package if my predictor is continuous?

I am trying to run mediation analysis to see if one continuous biological variable mediates the relationship between another continuous biological variable and a time-to-event survival outcome. I am ...
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transforming a continous respond variable into a discrete one

I am visually estimating fish length underwater to convert it in fish biomass by means of proper length-weight relationships. Obviously, my accuracy is not perfect. When making hypothesis about ...
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Discrete test statistics cannot form a uniform P-value?

I received this feedback on my permutation test design from a collaborator and I'm wondering if his claim is valid. My test statistics are discrete (like counting the number of red marbles found after ...
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Probability Theory (Jaynes' approach based on Cox theorem) CDF how to prove increasing monotonicity of this function?

In his book Probability Theory: the Logic of Science, Jaynes defines at page $107$ (chapter $4.5$) the continuous probability function. To do so, he introduces a real continuous "random" ...
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Choosing the right statistical analysis for my data

I have 20 field plots. In each plot, I have taken between 1000–1500 measurements (continuous values) of a given variable using an instrumental device and recorded information qualitatively through ...
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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 ...
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Which statistical tests should I use for predicting one variable with another one?

I want to investigate the association between the serum glucose level of a patient with type 2 diabetes at the baseline (continuous) and distal neuropathy (categorical), $5$ years after the diagnosis. ...
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Analysis method for comparison of means in zero-inflated non-paired continuous data

I am currently doing my first project involving a lot of statistics and I've stumbled into a bit of a problem. I am researching if comments from two different subreddits explainlikeimfive (ELI5) and ...
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How to account for spatial autocorrelation when the outcome (distance cycled) is continuous?

I aim to predict distance cycled based on population density, recreational area density, infrastructure density, road intersection density, and average gradient (hilliness). The response variable, ...
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Losing significance when adding variables to hierarchical regression model

I have two hierarchical models with continuous variables. In the first block, one of the variables is significant. However, in the second block, when I add three more variables the first variable ...
Statistics_3280's user avatar
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Correlation Coefficient between discrete and continuous: is it possible?

Is it correct to measure the correlation coefficient between a continuous variable and a discrete variable? I visualized it and there is definitely no linear relationship the way I see it that is why ...
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Psuedo-"Odds ratio" for multiple columns

I have a dataset with a categorical target ($y$) and multiple categorical features ($x_1$, $x_2$, ..., $x_i$). I have been able to successfully use a logistic regression model to calculate an odds ...
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Predictive Modeling of Overseas Filipino Workers' Average Length of Stay: A Comparison of Linear and Poisson Regression Models

i want to find our average length of stay in months with a discrete values however the number of months in the dataset is up to 60 that we can treat as continuous. I would like to determine when is ...
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Correlation between two groups over a set of treatments for a continuous value

I have two groups tested with a set of treatments, and the measured quantity is continuous. Is there a good way to compute the correlation between the two groups? For example, I have two types of ...
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How can I perform a comparison of poisson and linear modelling using one dataset?

my y is average length of stay in months however the number of months in dataset is up to 60 so I can treat it as continuous but my main objective is to identify when can i determine it's better to ...
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"Decade" variable ranging over 130 years - Can I treat this as continuous? I've seen it done with 8pt scales...but it doesn't past the smell test

My dataset includes "decade founded" but not "year founded" for organizations. I need to include some "maturity" variable in the model. Decade is the best I have. The ...
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Equating between short form and long form of the same instrument

I have encountered several instruments in psychology and related fields where we have multiple versions of the same instrument, specifically a short form and a long form. For instance, the patient ...
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Practically and probabilistically modeling discrete data that can take on a countable (potentially infinite) number of values?

As an example, let's say that we have observations of the price of some good at various points in time and would like to predict the distribution of the price of the good one point in the future from ...
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How to do a moderation analysis with dichotomous IV, continuous MV and continuous DV

I’m trying to do my data analysis (SPSS) for my thesis and I’ve been stuck for days. My supervisors also don’t know what test is best or they don’t respond to emails. I have 1 continuous MV (sleep ...
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Interpretation of multiple logistic regression (continuous variables) with interaction term

I have two independent variables, distance and light intensity (continuous variables) that I want to understand their ...
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Two-sample statistical significance test taking into account group membership (proportions) and numeric comparison

Say I have two samples of observations, S1 and S2, which can be of unequal sizes. For each observation, I have two variables: G (a categorical group assignment, say it is binary with values A/B), and ...
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Mixture Model: Data Consist of Continuous and Binary Features

I have a features like below id x1 x2 x3 x4 x5 id1 0.4 1.4 5.6 1 0 id2 -0.01 0.5 -3.4 0 1 where x1, x2, x3 are continuous features and x4 and x5 are binary. The goal is to find $k$ clusters using ...
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Help in identifying appropriate statistics to analyze repeated measures data with multiple trials

In a repeated measures design with multiple trials, what would be some appropriate statistical techniques used to analyze data when the variable of interest is a continuous variable? For example, let'...
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Using both discrete and continuous moves in Metropolis-Hastings

I want to sample a continuous distribution $f$ using the Metropolis-Hastings algorithm. Can I define my transition kernel as being sometimes discrete and sometimes continuous as long as I use the ...
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Converting a continuous metric to a proportion for increased power

I run online A/B tests and I guess I have some basic stats background, but I've encountered a situation where I don't feel confident about. We plan to track page load time in each experiment to make ...
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Dichotomizing a continuous predictor leading to differing effects on 2 outcomes

I am fairly new to statistics as a Phd student. I am trying to understand how dichotomizing a continuous variable can lead to distinct effects on two dependent variables. So in a cross-sectional ...
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Interpreting interactions in Cox Proportional Hazard models

I am currently doing an interactions paper with cox models to assess time to criminal recidivism as an outcome, but am struggling with the interpretations. My two variables that are part of the ...
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For a logistic regression, how to include continuous independent variable that also depends on binary independent variable?

Hi trying to better understand the statistical approach for the below problem. We'd like to build a logistic model (binary outcome) with two independent variables: one binary and the other continuous. ...
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Analyzing importance of continuous and categorical variables in linear regression in R

I am using R. I have a data set with a binary (0,1) response and both continuous and categorical predictors. I would like to test the overall importance of these predictors one by one, and I am ...
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2 or more continious features in Tree classification

If a training set has a continious feature, some texts recommend that first the dataset is sorted based on the continious feature, and then split points are chosen. What I am not sure about, is how ...
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Bayesian inference for continuous prior and discrete likelihood

I’m trying to wrap my head around an applied engineering problem which can be formulated in the following way. There is a black box which produces exponentially distributed events $E$ with random ...
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Is generation/evaluation of probabilistic predictions on continuous data feasible for larger data sets in practice?

To better capture uncertainty about the phenomena that we model, probabilistic predictions seem to be a natural and common extension of point predictions. Methods for evaluation of these predictions ...
QMath's user avatar
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What test is appropriate for a continuous dependent variable and 2 independent variables (one categorical and one continuous)?

I have fish data from 2 sites and am looking to see if there is a difference in some hormone concentrations (continuous) between the sites. However, it turned out the size of the fish differed between ...
MBerry's user avatar
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1 answer
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Why are interaction effects for categorical variables under our treatment not included?

We're trying to see the effects of treatments on the download speed of mobile data in 4 locations, with three variables: SIMs, Locations, and Time. SIMs has 2 factor levels, Locations has 4 factor ...
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Is my variable a discrete random variable, ordinal, or categorical?

I work in trauma research. We use a injury grading system that is fairly unique. Using a system developed in the 60s-70s - the Abbreviated Injury Scale - injuries are graded for six distinct body ...
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Can Pearson Correlation be Used Between Continuous and Dichotomous Variables for Feature Selection?

I'm working on a dataset that contains both continuous and dichotomous numerical features, the latter having values in the set $\{0, 1\}$. My objective is to apply feature selection to my dataset to ...
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How should I code a laboratory variable that may occasionally have "under X.XX" type of character data as a continuous numeric variable?

A typical laboratory in my region may give a result to e.g. the C-reactive protein (CRP) blood test in the following way (I'll omit the units here): if the result is under <10, they'll give the ...
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Interpreting interaction between a categorical and centered continuous variable (binary response)

In my model, in which I'm attempting to infer which covariates affect whether a fish has an empty stomach or not (1=empty, 0=not empty), I decided to grand-mean center the variable "SL" (...
Nate's user avatar
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How to detect categorical data masquerading as continuous? [closed]

Are there any known statistical methods or laws that can be applied towards the detection of categorical data masquerading as continuous? Categorical data can masquerade (or be "obfuscated" ...
Ian CT's user avatar
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1 answer
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How does a machine learning model distinguish between ordered discrete int and continuous int?

Lets say I am classifying if a user will like a Airbnb listing or not (binary classification model) I have 2 features: Number of house rules the Airbnb host has. Since this is a count, this is a ...
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Should all independent variables be transformed to fit Homoscedasticity in Linear Mixed Model?

I'm running Linear Mixed Models on a dataset. The assumption for homoscedasticity is not being met, however when I remove one independent variable, then it's being met. So all the other variables ...
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Can I combine two continuous variables to fit a linear mixed model?

Suppose a dataset as follows: ...
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