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SPSS: related-samples friedman's two-way analysis of variance by ranks extra bar in graph [closed]

I'm new here, and somewhat of a lay-user in terms of statistics, and hoping this question will be at the appropriate place. I'm running the mentioned analysis in SPSS on 3 iterations of an experiment ...
Ishkur's user avatar
  • 3
1 vote
2 answers
30 views

Should I conduct a multilevel for this or another analysis? Need help

I have three sources of data (teachers, parents and students) assessing students, in three waves. I want to assess all and see the differences between moments but then I also want to use variables for ...
Margarida Santos's user avatar
-1 votes
0 answers
8 views

what happens when a network has low closeness centrality - what happens to nodes on the periphery [closed]

I have thirty-nine nodes with closeness centrality scores but I do not know what to say about the nodes on the periphery who do not have scores.
user451331's user avatar
3 votes
1 answer
46 views

Calculate marginal effects for random effects model with two crossed random effects

I am trying to get effects marginal of two crossed random effects (using STAN or brms). I understand how to do it for a single random effect following McElreath's book and Kurtz's brms version of the ...
Christopher Rounds's user avatar
0 votes
0 answers
56 views

Alternative to Loglinear Analysis when Assumption are violated [closed]

I conducted a log linear analysis on a dataset where i have 3 categorical columns to compare so i can see if there is an effect of on others or a combination of two .... the description is here : ...
MexcelsiorB's user avatar
4 votes
2 answers
41 views

Accounting for non-independence and autocorrelation in HGAM

I am currently trying to fit a HGAM to model differences in daily activity patterns of fish in two treatments. Data were collected with high-resolution telemetry, and I currently have estimates of ...
Jack B's user avatar
  • 105
0 votes
1 answer
17 views

Looking for appropriate model to run on SPSS while accounting for multiple measurements on same subject

I have two groups (Group A and Group B) that have different baseline characteristics. All subjects go through 5 different weights (twice each) and an outcome variable is measured. The table below ...
Hassan Syed's user avatar
0 votes
0 answers
22 views

Derive gamma-parameters from preset R^2 in mixed models

For a simulation study in R, I want to select the effect sizes according to a preset $R^2$. Consider this two level random intercept mixed model, with one L1 predictor $X_{ij}$ and one L2 predictor $...
Linus's user avatar
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0 votes
0 answers
6 views

Analysis of GBS before and after COVID-19 while adjusting for confounding variables

I am new to statistics and would appreciate the help! I am using SPSS and am working on a project where I want to analyze the impact of COVID-19 on Group B Streptococcus (GBS). I therefore have 4 ...
Anna's user avatar
  • 1
0 votes
0 answers
9 views

Extracting individual level posterior class memebership probabilities in multilevel LCA

I am conducting a multilevel laten class analysis using the R package multilevLCA. I have fitted the model using multiple steps (i.e. determining optimal number of classes as well as clusters). I now ...
Simon's user avatar
  • 1
6 votes
1 answer
127 views

Is there a way to forecast by subgroup without forecasting each subgroup separately?

I am trying to find an appropriate model to forecast the number of applications received at the end of a recruitment cycle based on previous recruitment cycles and the number of applications received ...
Richard Manser's user avatar
1 vote
0 answers
50 views

Opposite results using Bayesian (STAN) vs Multilevel model (nlme). How is this possible?

My datasets contains the median wages and the cumulative installed wind-capacity for 4000 counties over a period of 20 years. The wages tend to rise over the period and the capacity tends to highly ...
user442239's user avatar
0 votes
0 answers
18 views

How to Forecast Sales for Sub-Locations Without Historical Proportion Data?

I have a time series dataset of total sales for a product in a store over time. This product is available in two different locations within the store: one stand near the checkout and another stand in ...
Raheshi Knuwga's user avatar
0 votes
0 answers
24 views

Multilevel Model in R

I have data from a study in which 19 participants (9 males, 10 females) have each completed 4 jumping conditions (BW, 20, 25, 30) whilst I have measured joint level data for the hip, knee and ankle. I ...
teli95's user avatar
  • 1
0 votes
1 answer
42 views

CWC(M) in multilevel modeling

I am new to multilevel modeling and recently learned about CWC(M) by Zhang et al. (2009, https://journals.sagepub.com/doi/abs/10.1177/1094428108327450). I am running a multitlevel moderated mediation ...
AUPW's user avatar
  • 1
0 votes
0 answers
12 views

mice multilevel imputation: does specifying cluster variable ("-2" in predictor Matrix) without multilevel methods lead to cluster robust imputation?

In short: Are mice's imputations cluster robust when I only specify the cluster variable with "-2" in the predictor matrix but do not use multilevel models during imputation? For clustered ...
JannisB's user avatar
1 vote
0 answers
57 views

What would be the best way to retain or impute data containing willing OR not willing to answer?

I want to impute missing data in a survey. In my dataset, participants could choose not to answer certain personal questions (e.g., age, family background), leading to both intentionally missing and ...
Marcus A.'s user avatar
2 votes
1 answer
48 views

Why factor scores correlated with variables do not equal loadings?

I am trying to understand the following: I have three variables (x1, x2, x3) on which I did PCA and EFA (principal axis factoring) in SPSS to get one component/factor. If I do PCA and I calculate ...
martin's user avatar
  • 41
4 votes
1 answer
45 views

How to Simulate a Multilevel Predictor Variable with Both L1 and L2 Variance Components?

I'm working on simulating multilevel data where I have a predictor variable measured at Level 1 (L1), which has both L1 and L2 variance components. For example, I want to simulate a socio-economic ...
Linus's user avatar
  • 153
2 votes
1 answer
35 views

Reporting Hierarchical Regression Results in Abstract

I did a hierarchical regression test in a social science study looking at how two variables (A and B) and their interaction term can predict variable C. My mentor told me to write in the abstract that ...
kangaroo123's user avatar
5 votes
2 answers
322 views

Should i recode data because of a difference in directionality of scales?

I have a dataset containing roughly 2500 respondents, with 63 variables. They are mostly responses to questionnaire questions. However, for example, one of the questions is "How often do you get ...
kubakubakuba's user avatar
0 votes
1 answer
33 views

Mediation models require a sigma matrix that is symmetric

I'm trying to fit the following reproducible mediation model called final. But I get an error saying: sigma must be a symmetric matrix Could you please advise how ...
Simon Harmel's user avatar
2 votes
0 answers
16 views

Which estimator to choose for meta-analysis^ REML or CR2 with Wild Bootstrap?

I am following the following book: https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/multilevel-ma.html I can't choose which estimator to choose: REML or CR2 with Wild Bootstrap. Or maybe ...
YuliaM's user avatar
  • 21
3 votes
1 answer
61 views

How can we simulate correlated random variables that vary at different levels in a multilevel/mixed effects setting?

I am very familiar with generating correlated random variables from a multivariate normal distribution. This question is about doing that in a multilevel setting, where variables only vary at ...
Robert Long's user avatar
  • 65.8k
2 votes
1 answer
78 views

General formula for mixed models

I'm trying to wrap my head around the general formula of mixed models and how it relates to the system of equations I'm used to. The general formula read like this: $$\mathbf{Y_{j}}=\mathbf{X_{j} \...
Linus's user avatar
  • 153
4 votes
1 answer
39 views

Outcome in mixed models - lower level or upper level?

I am learning about mixed models and I have a question regarding the outcomes that can be considered. If I have hierarchical data, do the outcomes that I can consider need to belong to the lower level?...
niqp's user avatar
  • 43
8 votes
1 answer
471 views

Power analysis for three-level multilevel models in R

For a study in a social science setting - where huge number of participants are not easily available - I'm trying to do a power analysis for a three-level multilevel design. There are few packages ...
Linus's user avatar
  • 153
1 vote
0 answers
19 views

modelling overdispersed binomial data using generalised linear models

I've run a series of tests where each test involves answering 10 questions which are scored correct/wrong, and there are roughly 36 participants per test divided more or less evenly into 3 treatment ...
Kavita Thomas's user avatar
1 vote
0 answers
15 views

How to Set Up a Polynomial Multilevel Model

I have a modeling situation that I am not 100% sure how to approach. I have two independent variables, information and time, with time being a repeated measure. The dependent measure is difference. ...
Gabrielle's user avatar
1 vote
1 answer
56 views

Multi-level modelling?

In an instructional study, I have pretest and post-test measures of writing quality--no control condition. There are 110 students nested in 10 classes. I have pretest measures of spelling skill and ...
pkleinuwoca's user avatar
1 vote
0 answers
62 views

Prediction Intervals With Hierarchical Regression Model

I'm reading this data analysis book by Gelman and Hill and am trying to understand predictions with hierarchical models. On page 273 they are demonstrating making new predictions for an already ...
RSHAP's user avatar
  • 133
0 votes
1 answer
103 views

Linear mixed-effect model analysis via python

I want to perform linear mixed-effect analyses for my research. I am trying to understand and compare the effect of 3 different intervention models on the outcome. I have 2 measures for the outcome, ...
user409631's user avatar
1 vote
0 answers
56 views

Error in lmerTest: The random-effects parameters and the residual variance (or scale parameter) are probably unidentifiable

I know that there have been similar questions before, but I dont still get it. I would like to estimate a multilevel model with repeated measures in R using the package “lmerTest”. The model ...
Ineluki's user avatar
  • 11
2 votes
0 answers
19 views

Hierarchical models where the hierarchy structure depends on a latent variable

I am having trouble formulating a hierarchical model for the purpose of Bayesian inference in the case where the actual hierarchical structure depends on a latent variable. I am wondering if this is ...
gabe's user avatar
  • 131
2 votes
0 answers
39 views

Can I Perform a Micro Synthetic Control Analysis with Different Aggregation Levels for Treatment and Control Groups?

I am conducting an analysis using the microsynth package in R to evaluate the impact of increased police presence on various outcome measures obtained from an official survey. My treatment areas ...
DeMelkbroer's user avatar
0 votes
0 answers
11 views

Fitting nonlinear Bayesian regression with a summation term in brms

I'm trying to fit parameters for a Holling type II curve for multiple prey items. This takes the form: $$ \frac{dP_i}{dt} = \frac{a_iP_i}{1 +\sum_j{a_jh_jP_j}} $$ where $P_i$ is density of prey ...
Jacob Weverka's user avatar
0 votes
0 answers
37 views

Categories automatically dropped in SPSS for my logistic regression [duplicate]

I have a problem with my logistic regression model. I use SPSS for analyzing the relationship between some categorical IV/2 numerical variables and customer churn (the well-known IBM Telco dataset). I ...
Zevion's user avatar
  • 1
1 vote
1 answer
26 views

Setting predictor variables with 3-levels in multilevel mode

I am working with a random intercept multilevel modeling. I want to predict general health based on survey data. The survey uses nested data set on three levels: individual, county, and state. I am ...
YouLocalRUser's user avatar
3 votes
1 answer
48 views

Mixed Model: Translation from mathematical notation to R's lmer() - package: lmerTest

The following data should be generated and fitted to a mixed model (for further simulation studies): $y$: outcome of clinical study (effect of medication) indiv individuals = 20 repl replicate ...
m09s19's user avatar
  • 95
1 vote
2 answers
35 views

About adding random effects in Multilevel (HLM) analysis

I am doing regression analysis in HLM. I am wondering whether random effects should be added in this process. Let me ask a question using a famous example. LV1 is a student and LV2 is a school. LV1 ...
Nobody Nobody's user avatar
2 votes
1 answer
35 views

Experimental condition with multilevel model

I am working with a survey experiment. The data is set at three levels: individual, county, and state. The experimental condition was randomized at the individual level 1. That is, some individuals in ...
YouLocalRUser's user avatar
0 votes
0 answers
63 views

non-negative constraints and interactions in the ensemble model

In the context of prediction problems using regression models, suppose I have $K$ different models all trained (fitted) on the same targets (observations). These models are different - low correlation ...
jam123's user avatar
  • 1
0 votes
1 answer
31 views

Discrepancy in manually calculated Kendall's tau-b vs SPSS output

stats enthusiasts! I'm having trouble with a manual calculation of Kendall's tau-b. My result differs from the SPSS output, and I can't figure out where I went wrong. Here's my process: I'm analyzing ...
isaaclt's user avatar
0 votes
0 answers
28 views

How should i correct my classification table in logistic regression? [duplicate]

The omnibus tests of model coefficients show that the model is significant. However, the classification table under Block 1 shows the same ratio of observed to predicted values as Block 0. Does this ...
Fatima's user avatar
  • 1
0 votes
0 answers
25 views

3-level clustering in Multilevel Latent Class Analysis of distal outcomes

I am investigating the relationship between latent classes of student experiences (also aggregated on the school level) and student achievement based on the PISA data (cross-sectional, continuous ‘...
Piotr Lipiński's user avatar
1 vote
1 answer
32 views

Propagating measurement uncertainty with posterior predictions as data in another model

I'm working on a modeling approach that incorporated estimates of measurement uncertainty trying to use brms in R. I'm working from the example in chapter 14 of ...
Jacob Weverka's user avatar
0 votes
1 answer
34 views

Can I do weighting on continuous variables?

I have two datasets collected in 2018 and 2023. I was going to check if there's any difference between the two datasets, but the ratio of sex and family size was different from each other (...
BEAU's user avatar
  • 1
1 vote
0 answers
38 views

Multilevel model where skew of random effect depends on an independent variable

I am trying to construct a model where the skew of the distribution of a random effect changes with an independent variable. I'd eventually like to fit this using ...
Jacob Weverka's user avatar
4 votes
1 answer
33 views

Mixed model (random effects) vs pooled OLS with clustered SE

I have a dataset of country-years. I want to find out whether membership in a particular group, say, EU, has an effect on an outcome, say, GDP. In my initial model, I estimated a pooled OLS model with ...
taylor's user avatar
  • 41
0 votes
1 answer
35 views

Hierarchical logistic regression interaction

looking for some guidance on analyses. I'm running hierarchical logistic regression models with a cross-level interaction, x and z (both variables are continuous). Even though the interaction is not ...
whydidistartthis's user avatar

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