Causality and Variable Relationships
Explore concepts like causality, bivariate associations, and probabilistic relationships in variables. Understand the significance of Non-linear relationships, Spurious relationships, and the role of Independent and Dependent variables. Learn about different measurement levels of variables and how they impact the relationships.
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Presentation Transcript
CONCEPTS TO BE INCLUDED Causality (Non-)linear relationship Spurious relationship (causal) hypothesis Sign or direction (of a causal relationship) Bivariate Probabilistic Deterministic Dependent variable Independent variable 1 4/19/2025 Footer text: to modify choose Insert (or View for office 2003 or earlier) then Header and Footer
BIVARIATE ASSOCIATIONS HENK VAN DER KOLK
AIM Causality: Time order, Association, Non-spurious relationship. Bivariate associations between variables with various levels of measurement. 3
A RELATIONSHIP BETWEEN TWO VARIABLES Exogenous concept Cause X-variable Independent variable Treatment Endogenous concept Effect / Consequence Y-variable Dependent variable Observation 4
CAUSALITY IN A GRAPH Positive Dependent variable SIGN Negative Independent variable 5
Non linear: parabolic Non linear: quadratic Dependent variable Linear negative Independent variable 6
PROBABILISTIC Deterministic: If then always Probabilistic: If then relatively more/less often 7
PROBABILISTIC CAUSALITY IN A GRAPH 7 6 5 4 3 2 1 0 0 2 4 6 8 10 12 14 16 8
WHY PROBABILISTIC ONLY? Measurement error Parsimoneous models: omitted variables 9
MEASUREMENT LEVELS OF VARIABLES Dichotomous Gender (male, female) of a person Nominal Country in which the headquarter of a company is located Innovative power of a company (low, medium, high) IQ scores of employees Profits or losses of a company Ordinal Interval Ratio 10
RELATING VARIABLES Using graphs to show causal relationships works fine when using interval - or ratio level variables. How to show the relationship between dichtomous and nominal variables? 11
PROBABILISTIC CAUSALITY IN A TABLE Two dichotomous variables Independent variable A B Total Dependent I X x variable II X x Total 12
PROBABILISTIC CAUSALITY IN A TABLE Two ordinal variables, or nominal variables (with columns and rows ordered by expectation) Independent variable B A C X Total I x x Dependent II III X variable x x X x x Total 13
THIS MICRO LECTURE Causality: Time order, Association, Non-spurious relationship. Bivariate associations between independent and dependent variables with various levels of measurement 14
15 4/19/2025 Footer text: to modify choose Insert (or View for office 2003 or earlier) then Header and Footer
