Publications by Anna Shirokanova & Olesya Volchenko
Correlation in R
Correlation analysis: practice Anna Shirokanova & Olesya Volchenko March 13, 2023 This seminar Recap of correlation analysis Examples of correlation analysis Types of correlation How to report correlation results Correlations Probably the most widely spread statistical concept Also widely misused Devised to estimate the relationship between t...
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One-way analysis of variance (ANOVA) in R
One-way analysis of variance (ANOVA) in R Anna Shirokanova and Olesya Volchenko February 27, 2023 This seminar Recap of one-way ANOVA Example of one-way ANOVA assumptions post hoc tests Non-parametric equivalent of ANOVA Effect size ANOVA is used: to compare means of three or more independent (unrelated) groups and determine whether they ar...
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Document
Comparing Two Means Anna Shirokanova and Olesya Volchenko Fubruary 13, 2023 Let’s compare mean values Mean values refer to continuous variables. Mean values can be compared across groups. If there are two groups, t-test is the parametric test you need to make a conclusion about the two populations. If there are more than two groups, use one-w...
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ANOVA 2 примера
База данных со случаями возникновением рака молочной железы. Включает следующие переменные: country (страна) continent (континент) year (год) lifeExp (ожидаемая продолдительность жизни) pop (население) gdpPerca...
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Multilevel modelling: empty model
First, a few words about the dataset. It is a joint dataset containing the latest rounds of EVS and WVS. The dataset contains information on 127358 respondents from data0 <- read.csv("wvsevs_lifesat.csv") In the first example, we are going to use life satisfaction as a dependent variable. summary(data0$lifesat) ## Min. 1st Qu. Median Mean ...
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Multilevel modelling: adding and randomizing individual level predictors
So, last time we estimated an empty model with life satisfaction as a DV. ICC of the model (0.12 or 12%) indicated that multilevel modeling is recommended here. So, let’s proceed. Let’s say we want to model the relationship between life satisfaction and religiosity using a set of socio-demographic variables as controls. data0 <- read.csv("wvs...
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Multilevel modeling: full model
data0 <- read.csv("wvsevs_lifesat.csv") So far we have completely ignored possible country-level predictors. All of the predictors have been measured on the lowest level (in our case, individual). Today we will change that! Another thing that we have not reflected upon is how to explain the observed difference in the slopes. We also will try to d...
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Interactions
Linear Regression with Interaction Effects Anna Shirokanova, Olesya Volchenko 5/13/2020 This seminar: Interaction effects: Exercise 1. Categorical by continuous Exercise 2. Categorical by categorical Exercise 3. Continuous by continuous Example from the European Social Survey data, Wave 7 Variables involved: alcwdy : Grams alcohol, last tim...
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Regression
Regression: Not Only a Mystery Thriller Olesya Volchenko and Anna Shirokanova May 13, 2021 What do we already know? test association between two categorical variables (chi-square) find relationships between categorical and continuous variables (ANOVA, t-test) test relationships between two continuous variables (correlations) Why do we need r...
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Chi squared
Chi squared Anna Shirokanova and Olesya Volchenko February 15, 2022 Two Categorical Variables: Pearson’s Chi-Square Test it is a test of proportions requires a contingency table as input (raw data in counts, not per cent) at least 5 expected observations per cell for small groups (<5 observations/group), use Fisher’s exact test, 2*2 each ...
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