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Questions tagged [mixed-type-data]

Dataset including variables of different measurement nature (e.g. continuous, categorical, binary, count etc.) analyzed together in one variable set. Use this tag when this presents a challenge for the analysis. Do NOT use to refer to [mixed-model].

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Appropriate datatype for cyclical periods (like days of the week and seasons) [duplicate]

I am trying to figure out the best way to encode cyclical time indicators like days of the week and seasons. (Other examples would be day of the month and week of the year, but I'll try to keep this ...
Tripartio's user avatar
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3 votes
1 answer
140 views

Can MCMC sample any probability distributions?

I have three fundamental questions related to MCMC. I would appreciate the help on any one of those. The most fundamental question in MCMC field, which I can't find a reference, is: Can MCMC generate ...
George Lu's user avatar
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1 answer
42 views

multivariate meta-analysis - can subgroup indicator reflect several different variables and outcome types?

I have seen that in meta - analysis, a multivariate model can be used to get the same estimates as a series of separate meta analyses e.g. https://www.metafor-project.org/doku.php/tips:...
user167591's user avatar
2 votes
1 answer
73 views

Different baseline data for sites [closed]

I have the data with 2 treatments and 1 site (see the image). I am trying to run a mixed model with the code below. ...
Ahsan Mir Rajper's user avatar
2 votes
1 answer
102 views

Chi square test (or alternative) for mixed design categorical data

I have the following question: I collected the number of different symptoms at two time points (Baseline BL, Follow-up FU) in two groups (Control Group CG, Intervention Group IG). So, there is a ...
Manuel Leitner's user avatar
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20 views

Hierarchical cluster analysis with mixed data

I have a dataset consisting of 134 observations and four variables. The dataset consists of answers to a questionnaire. I want to perform a hierarchical cluster analysis on the variables in the ...
Lasse H's user avatar
1 vote
0 answers
27 views

Which model should be used to analyze repeated measures in the context of survival meta-analysis?

I am in the following context: each patient has at least 2 measurements, but possibly more (up to 5 measurements), of a given biomarker. The first measurement is taken at baseline, but the date and ...
Flora Grappelli's user avatar
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19 views

Conditions of the covariance matrix between discrete and continuous variables

Does the covariance matrix for a discrete variable and a set of continuous variables have extra constraints beyond being positive semi-definite as in the case of a real-valued random vector? ...
Sergio's user avatar
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0 answers
35 views

mixed effect model question

Hi i have a certain task i want to solve: For two months, participants played an app, in which they played 5 different therapeutic games (TGs). At the beginning of each session, they also completed a ...
nof's user avatar
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3 votes
1 answer
61 views

What is mixed methods research?

I tried to look up the answer but am confused by what this means exactly. It seems like one is a precursor to the other, thus you need both to conduct a study unless you're working with existing data. ...
jon's user avatar
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5 votes
2 answers
216 views

Should I pool multiple observations from the same experimental unit, or use mixed effects models

I am trying to assess the effects of an experimental treatment on the insect fauna of artificial ponds. The treatment is applied to the entire pond. I was able to sample each pond four times, each ...
Rodolfo Pelinson's user avatar
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38 views

How to quantify the dissimilarity across different types of variables?

I have two dataframes with the same columns but with varying sample sizes. I want to compare corresponding columns for homogeneity (i.e., do they come from the same distribution?). There are different ...
Glue's user avatar
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0 answers
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Clustering mixed data - SPSS [closed]

On my current project, I have to form four or five clusters describing different types of banking customers. The data is based on a survey of around 3500 participants and contains more than 250 ...
user380310's user avatar
1 vote
0 answers
100 views

Fractional factorial design with mixed categorical and numerical variables analysis for more than two levels

I have an experiment setup that consists of multiple continuous and multiple categorical variables. Right now, I am just using two levels for the categorical variables, allowing me to encode them as -...
Jofkos's user avatar
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2 votes
0 answers
328 views

Multilevel/ Mixed Model / HLM Centering Interactions Level 1 and Level 2 Cross-Level

I am having some trouble with the literature on the correct model specification for my question. Here is the setup: I have a multilevel model with a variety of variables at level 1 and a single level ...
bzh's user avatar
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Does persistent homology really make sense for mixed variable types?

Purpose Persistent homology is a fascinating approach to exploring data (see Chazal & Michel 2021 for an introduction). I have seen many impressive examples of it through AATRN. I'm considering ...
Galen's user avatar
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1 vote
1 answer
235 views

Is applying dimension reduction to mixed type data valid for outlier detection after that?

I'm facing with anomaly detection (outlier detection) task with mixed (numerical and categorical) multi-feature data set. I understand that many of the possible multivariate outlier detection methods ...
Hendrik's user avatar
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90 views

Likelihood of mixed discrete-continuous data

I'm struggling with the derivation of the likelihood with mixed continuous and discrete variables. Let us take this simple example: \begin{align*} X &= \begin{cases} 0 & \text{with ...
G. Ander's user avatar
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1 answer
24 views

High Performance Classification or Similarity Algorithim for Mixed Data Types?

I have a database holding 10-ish features that describe different breeds of dogs. They are mostly categorical features, but some provide ranges for values. Here's a demo representation of the database,...
CyberBully2003's user avatar
2 votes
1 answer
714 views

How to choose a fair gamma value when performing k-prototypes clustering?

In the k-prototypes clustering algorithm, the distance function consists of two dissimilarity components - one for the numerical elements of the observations, and one for their categorical elements. ...
Emilien's user avatar
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0 answers
387 views

PCA or Drop high correlated variables for clustering

I am performing clustering on mixed data type. I have few features which are high correlated. We generally use PCA before clustering and reduce the feature space, as its a mixed data I have used FAMD ...
Anilaaryan's user avatar
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1 answer
293 views

What is the data type of speed limit of a road network segment?

As you know the data type is one of the most important factors in selecting the Machine Learning algorithm. For example, K-means should not be employed for categorical data. I have a csv file ...
Asa Ya's user avatar
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92 views

Clustering a dataset with mixed, skewed, semi-correlated and unscaled values

I have a dataset containing six features, around 13000 records, and representing an urban road network. I imported data as a dataframe into Jupyter and table below demonstrates the sample of this data....
Asa Ya's user avatar
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0 votes
0 answers
183 views

Weighted metric for mixed binary (decomposed) data?

I have a large dataset with mixed type of data (example): Age Price Town Size Interests Small Middle Big Traveling Cooking TV 21 0 1 0 0 1 1 1 34 100 0 1 0 0 1 0 81 200 0 0 1 1 1 0 54 0 0 0 1 1 ...
user327865's user avatar
1 vote
0 answers
23 views

Best option for calculating distance/similarity for structured data with both categorical and numerical dimensions?

Say you have individual one with the following attributes: {age: 25, gender: Male, education: Bachelor's, residence: California, salary: 65,000}. Individual two has the following attributes: {age: 27, ...
NominalSystems's user avatar
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0 answers
31 views

Should I aggregate explanatory variable?

The dataset I have is an aggregated outcome, e.g., the quarterly revenue of each firm (that manages a number of plants), revenue is measured by the end of each quarter a focal explanatory variable, e....
user001's user avatar
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0 answers
591 views

Co-relation between non numeric and numeric variable

I am not good at stats. So accept my apology in advance if my question sounds silly or trivial. I have two data sets. One contains the positive reviews of the app which includes rating given by the ...
user2293224's user avatar
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0 answers
33 views

Calculation of Correlation Matrix

If we have continuoues variables $X_{1},X_{2}$ and categorical variables $C_{1},C_{2}$ (with $L+1$ levels each $C_{i}$) variables, how do we define a Correlation Matrix where we have independence ...
Fiodor1234's user avatar
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1 vote
2 answers
3k views

Treat year as a fixed effect, random effect, or covariate?

I have a dataset of fish species from different sites within a harbour collected over 17 years. The dataset consists of 1,042 sampling transects collected at 6 specific locations where fish were ...
Dugan 's user avatar
  • 147
0 votes
1 answer
287 views

Can machine learning be used with data where each dimension is different?

Let's suppose that I have some data, and I have a vector representation of each data point. For example, one data point might look like this: [0, 1, 0, 3, -2, 2.3]. Now suppose that for each vector, ...
JBraha's user avatar
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0 answers
399 views

Testing for Collinearity in a Dataset with Categorical and Continuous Variables

I have a dataset that has 17 variables. 9 categorical and 8 continuous. Some have more than 2 levels. I've reduced the dimensionality significantly. I am looking for strategies to test for colinearity ...
Randy B.'s user avatar
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5 votes
2 answers
3k views

Why is betareg() giving "invalid dependent variable" error?

I am trying to run a beta regression using the betareg package and I am using the following script: ...
JKO's user avatar
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4 votes
0 answers
94 views

This mixed-type family of random variables has no dominating measure, so a likelihood function can't be defined?

Let $$ X = \begin{cases}\theta & \text{with probability 1/2}\\ Z\sim N(0,1) & \text{with probability 1/2.} \end{cases}$$ Here, $\theta\in\mathbb{R}$ is the parameter to be estimated. It ...
xce's user avatar
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1 vote
1 answer
309 views

What is a natural way to define RKHS over mixed spaces (discrete and continuous)?

It is well known that given a kernel $k$ over any space $\mathcal{X}$, there is a corresponding RKHS (Reproducing Kernel Hilbert Space) associated with the kernel $k$. For example, Radial basis ...
randomprime's user avatar
1 vote
0 answers
53 views

Categorical x continuous variable interaction in regression?

I have a sample containing two subgroups and I would like to measure the relationship between two continuous variables across the entire group and check if there's an interaction with subgroup. First, ...
EmbarrasedBadger's user avatar
1 vote
0 answers
699 views

What is the difference between a factorial analysis for mixed data (FAMD) and a PCA on a dataset where qualitative variable are dummy-encoded?

There are many variants of the principal component analysis (PCA) framework for discrete variables or a mixture of quantitative and discrete variables. Image from this book. However, I am not ...
Arthur's user avatar
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1 vote
0 answers
320 views

Robust RM ANOVA [closed]

I am an R beginner and I needed to run robust two way mixed ANOVAs with R using the WRS2 package and the function btwin because my data has nonnormal residuals (I looked at Q-Q plots) and there is a ...
0tonin's user avatar
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0 votes
0 answers
74 views

Factor analysis when I have mixture of continuous and dichotomous variables

I am trying to determine if there is a significant difference between two groups for a single continuous variable while accounting for baseline differences in dichotomous variables in each group. To ...
PabloCohen's user avatar
2 votes
1 answer
3k views

What post-hoc test should be used for a glmer model with a binary response, and a continuous and categorical predictor?

I'm a bit of a newbie with stats and R, so need a bit of direction to find a suitable post-hoc test for my glmer model. I'm trying to find if presence is affected by environmental factors for each ...
Madi 's user avatar
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0 votes
1 answer
1k views

PCR after PCA with mixed data - how to extract/export the PCs as new variables in R?

As the title/question implies I ran a PCA with mixed data, i.e. categorical and numeric, in R, once with the "FactoMineR" and "factoextra" packages (analysis version 1) and once with the "PCAmixdata" ...
daedhalus's user avatar
1 vote
0 answers
43 views

Scaling for mixed data and reverse transform

I have mixed type data (numerical, one hot encoded, ordinal). My data also has outliers. I am trying to scale them using a StandardScaler from sklearn, but I also need to revese transform the test ...
nicnaz's user avatar
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0 votes
0 answers
151 views

Self organized maps on mixed dataset (categoricals / numerics features )

i have a dataset of mixed variables and i want to apply self organized maps on it how can i extend som to mixed dataset? can i use the gower distance instead of euclidienne distance in order to ...
FATMA Boubekeur's user avatar
0 votes
0 answers
131 views

How to prove properties about mixed (discrete and continuous inputs) function spaces?

I am using Gaussian Processes for data with mixed inputs (discrete and continuous input variables) i.e. $π‘₯=[π‘₯_𝑐,π‘₯_𝑑]$ where $π‘₯_𝑐 \in \Re$ and $x_d \in \mathbb{Z}$. There is a lot of work on ...
randomprime's user avatar
1 vote
0 answers
696 views

How to use filter-based feature selection for mixed data types?

The idea behind filter-based methods of feature selection is that we assign a value to each feature, where the value indicates how important the feature is for predicting the outcome variable. We can ...
methus's user avatar
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1 vote
1 answer
683 views

Two way ANOVA when one independant variable is not Categorical

I am doing a test on doctors' training level and the number on duty. One IV is training level, the other IV is the number of doctors on duty. The DV is the number of patients seen. There are two ...
CarrotCakeIsYum's user avatar
2 votes
1 answer
1k views

Mixture model on binary + continuous data

If I have a dataset of continuous variables (that I can assume are normally distributed), I can identify subgroups using a Gaussian mixture model and implement. Likewise if I have binary data I can ...
Stuart Lacy's user avatar
0 votes
0 answers
37 views

Clustering algorithm for mixed data with non constant categorical variables

I have the following scenario, imagine that I have a dataset as follows: ...
Oliver's user avatar
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1 vote
2 answers
439 views

Statistical test to find association between two variables

I'm dealing with ecological data. Broadly speaking, i've counted the plant abundance (discrete variable) in a number of points (small blocks,one number for each ...
Denis's user avatar
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1 vote
0 answers
646 views

Input data for Canonical Correspondence Analysis (CCA)

I'm going to conduct Canonical Correspondence Analysis (CCA). In the tutorial I've found at: CCA environmental data are discrete ...
Denis's user avatar
  • 439
1 vote
2 answers
88 views

Determination of statistically relevant quantitative/qualitative variables

I have a database containing records of several parameters: one is a quantitative parameter $D$ (e.g. average fuel consumption), others are qualtitative parameters $X_1, ..., X_n$ (e.g. make, color, ...
Longbow4685's user avatar