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 ...

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11 views

Applying Cox Proportional Hazards Model on Discontinuous Variable

I am using coxph in Rstudio to apply Cox Proportional hazards model on my data. This model is easy to use on continuous variable ...
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14 views

Measure relationship between continuous variable & unbalanced binary variable

I am trying to select variables for modelling a binary variable (whether a person will repay a loan) using various continuous variables about them - age, income, years of education, etc. I'd like to ...
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1answer
82 views
+50

Categorizing Continuous Random Variable in Logistic Regression

I have a Bernoulli response variable and I am going to fit a logistic regression. One of my independent variables is a continuous random variable and I would like to categorize it before fitting the ...
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1answer
15 views

How to deal with quasi-continuous features?

I've searched around a bit for strategies to approach the problem I'm facing and haven't come up with much. I'm working with a data set that has many "quasi-continuous" features. That is, the ...
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0answers
25 views

How to calculate odds ratio per unit decrease of continuous variable

I have a logistic regression model obtained in R comparing association between two index diagnoses (0 or 1) with Age (continuous) + ...
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0answers
16 views

How to set sum contrasts for unbalanced factors

Let's say that I have a model where the response time depends on accuracy (0/1, coded either as categorical or numerical) and another categorical variable (pres: idem/diff), both interacting with the ...
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2answers
59 views

Gibbs sampling and mixed distribution

For a project, I need to simulate from a joint distribution with both continuous and discrete variables that are dependent. The conditional distribution of any variable given the rest is known. I ...
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2answers
28 views

Marginal likelihood: why integration is used

From wiki: Given a set of independent identically distributed data points $\mathbb{X}=(x_1,\ldots,x_n)$, where $x_i \sim p(x_i|\theta)$ according to some probability distribution parameterized ...
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20 views

Double Hurdle model with continuous DV and two sources of zeros

I want to regress a data set that contains a lot of zero's (~55%) and is determined by a typical 2-stage decision process generating the zeros: Consumer decides to apply for a bank loan or not (0-1) ...
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27 views

Moderated Correlation

I am interested in the moderation of a latent correlation. The model consists of two latent variables with three and four indicators. The latent variables are correlated and influenced by a continuous ...
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1answer
33 views

How do I find the percentile p (or quantile q) from a weighted dataset?

Say I have height measurements of Earth's population expressed with a precision of integer centimetres. ...
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13 views

Correlation between binary predictor and numerical response using Linear Regression

I am trying to find correlations between several binary predictors and a continuous response variable. I am not sure what test it is supposed to work for this case, I got confused with all the things ...
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21 views

compute likelihood

How can I compute the likelihood or posterior probability on data when the distribution function is continuous. For example the dist. function is a Gaussian and I have one hundred data points. Now how ...
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27 views

Interpretation of continuous by continuous interaction in binary regression model

I'm performing binary logistic regression in SPSS; y is dichotomous variable; and both Xs are continuous variables. I performed three models and I have troubles interpreting model with both ...
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7 views

Filter Feature Selection approaches for continuous variables?

I've noticed that correlation-based filtering for selecting features in high dimensional data require discretization of continuous variables, like e.g. Fast Correlation-based Filtering or regular CFS. ...
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0answers
33 views

Can you explain why this distribution has been suggested for the length of a telephone call

I don't understand what the distribution in e) shows me? I would expect a normal curve about the mean but this is confusing
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12 views

PCA for mixed variables

I have a dataset which contains many variables : continuous and discrete variables. I have a discrete variable adress which can include many value (if for example the customer changes his location, ...
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1answer
32 views

Discrete or continuous variable

I am trying to model Ip adress to cretae a fraud detection framework. So I am wondering if Ip Adress is a continuous or discrete or categorical variable. Bests
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30 views

Four standard deviation rules in relation to normality testing

Within our department we were given a set of guidelines for how we might decide whether to proceed with parametric or non-parametric testing (for continuous data). These were drawn up in consultation ...
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22 views

What analysis to use? IV: multiple interdependent levels, DV: continuous variable

My dependent variable is a continuous variable, ranging from 0 to infinity. However, my independent variable has multiple interdependent levels. To illustrate, A person has 6 attributes: A1, A2,... ...
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16 views

The marginal likelihood of a fully-observed continuous time Markov chain

Say we have a fully observed trajectory $S$ from a CTMC. For a generator/rate matrix $Q$, we place gamma priors $\mathrm{Gamma}(\alpha_{1},\alpha_{2})$ on the diagonals, and ...
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24 views

Get most occurring value on a graph

I have a data series which is continuous (there is data in between individual data points not captured by the series). There are many inflection points within the series and my goal is to find 5 most ...
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1answer
33 views

Deriving Formula for Marginal Distributions

I'm having trouble understanding exactly why when you have a two-dimensional random variable $(X,Y)$ and you want to find the marginal probability distribution of X, for example, you integrate the ...
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0answers
16 views

Transformations possible when performing a single multivariate ANOVA on a continuous and categorical species database?

I want to study the impact of aquaculture on a hard rocky seafloor community which is naturally low in diversity. 4 replicate images (0.25 m2 each) were taken at fixed distances (0, 20, 40, 80, 120, ...
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11 views

Relationship between categorical & 5 quantitative variables

Im a bit of statistics noob so Im hoping someone here can help me Im doing a research papaer where I've created a virtual market asking the participants which solutions they would like to invest in. ...
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16 views

Using ordinal variable as continuous variable in MLM

In this post, Can I use multiple regression when I have mixed categorical and continuous predictors?, it is stated that you can use an ordinal IV as a continuous IV in a multilevel model. Does anyone ...
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25 views

Using a variable as a continuous predictor in regression even if a middle range of values is missing?

I've been collecting data (various measures) in people with a body mass index (BMI) in the "healthy weight" range (BMI between 18.5 and 25) and the "obese weight" range (BMI over 30) (hence, I've ...
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82 views

How to transform ordinal categorical income into a continuous variable?

I have a large data set including an ordinal categorical income variable and want to transform this variable into a continuous variable. I want to perform a simulation study with the dataset and ...
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1answer
30 views

Chi-squared test for continuous variables (averages)

i'm trying to find a suitable statical test for my situation. The best way I can think of describe it is finding a Chi-Squared test for continuous data. Please tell me otherwise. Here is my made up ...
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1answer
34 views

How to handle continous data with several peaks

I'm running a simulation that produces continuous data distributed in 4 to 6 peaks. Each peak is roughly normally distributed. I'd like to detect each peak mean value and relative weight. Right now ...
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1answer
282 views

Is it ever a good idea to give “partial credit” (continuous outcome) in training a logistic regression?

I am training a logistic regression to predict which runners are most likely to finish a grueling endurance race. Very few runners complete this race, so I have severe class imbalance and a small ...
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1answer
25 views

Generalised linear models error distribution (continuous response)

I'm a bit confused about what error distribution I should use for the generalised linear models that I am running. My response variable is litter decay rate (k) (continuous, which runs from -1.5 to ...
3
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0answers
20 views

What is the best way to simultaneously fit multiple binomial and continuous predictors?

What is the most efficient way to fit a linear model w so that Y = w . X, where X is a ...
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0answers
21 views

Should time be categorical or continuous in a repeated measures model?

What is the difference between using time as a categorical variable (vs continuous) in a repeated measures analysis? When is one approach preferable to the other?
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2answers
62 views

Calculate probability distribution table for dates

I'm a software developer. Over 10 weeks our team has had the following estimations/actuals for how much work we can complete in points: ...
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0answers
17 views

Discretization for a bayes network model with small sample

I have been playing around with a Bayesian network toolbox for prediction and classification. I have had good success with the examples but I'm now stuck on how I should proceed with my scenario. I ...
3
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1answer
45 views

Probability two people arrive at the same time?

Two people arrive at a train station at a random time between 12pm and 1pm. They arrive independently of each other and their arrival times are uniformly distributed. What is the probability they ...
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54 views

Regression modelling with mixed data set: categorical and numerical predictor variables

There are thirteen predictor variables which are a combination of 8 continuous, 4 binary and 1 categorical variables. The dependent variable is again categorical. I understand that I need to use dummy ...
0
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1answer
39 views

Effects in metaanalysis forest plots - what are the conclusions?

In metaanalysis results are often reported in forest plots, where multiple studies are included. Different, continuous outcome scales are used to measure the effect of a treatment on the course of a ...
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33 views

Regression for continuous dependent variable with independent ordinal variable

My situation is as follows: as a teacher, I've given students the option to make 5 sets of homework during the year, which does not count for their grade, but solely to practice and receive feedback; ...
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0answers
21 views

How to compute a mean of some numbers from normal distribution? (using continuity correction) [closed]

In practice, specifically writing a paper, we often need to compute an expected value of some sample drawn from a certain continuous distribution. Let's say, draw 100 numbers from $N(0,1)$, and ...
1
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1answer
52 views

SEM: Combining latent and manifest variables

I did a survey, using many intervall-scaled items representing several constructs. I want to use these constructs to predict an outcome (decision: yes/no). Thus, I got (latent) predictors to explain ...
1
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1answer
57 views

Find P(Y=y | X=x) when X is a continuous random variable

could someone help me understand how to find the probability $\Pr(F=f_1 | X=x)$ by using the inputs below, where $X$ is a continuous random variable? Note: I know that probabilities of specific ...
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2answers
76 views

E(x) for uniform distribution

I would like to take a uniform distribution for example. Let’s say a train will arrive at the station randomly within every 10 minute window, so the probability density function is $f(t)=0.1$,$\: t ...
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0answers
36 views

Proper regression method for multiple continuous independent and a single continuous dependent variable?

I have 3 continuous (actually ordinal) independent variables and a single continuous dependent variable. I'm trying to sort out which regression method I should use in this case. MANOVA appears to ...
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0answers
25 views

Gamma/ inverse.gaussian glmer with zeroes that matter

I'm trying to analyze continuous non-negative data with real zeroes that matter. The data are either gamma or inverse.gaussian distributed (from gamlss package) and ...
0
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1answer
25 views

Count Models for Continuous variables

I want to analyze the effect of taxes on the amount of fixed assets an affiliate of an multinational capitalizes. Fixed assets are of course not a count variable. Can I anyway use a count model such ...
0
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0answers
21 views

How to find Kolmogorov Forward Equations, given generator matrix Q? [duplicate]

I am having difficulty in forming Kolmogorov Forward Equations. I understand how the KFE is derived and that $$\frac{d}{ds} p_{ij} (s) = \sum_{k \neq j} p_{ik} (s) \lambda_{k} r_{kj} - p_{ij} ...
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0answers
23 views

Find all modes (or modal intervals) in a continuous univariate sample

Consider a continuous random variable with density something like: There exist formal statistical tests for a sample from such a distribution which give us an indication of whether or not that ...
3
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1answer
37 views

How is it logically possible to sample a single value from a continuous distribution?

For example, suppose I am told that 10 data points come IID from a normal distribution with some mean and variance. Isn't the probability of realizing each of these values zero? Shouldn't the fact ...