Download presentation

Presentation is loading. Please wait.

Published bySergio Bowns Modified over 4 years ago

1
I. The Definition of Causation Causation II. The Statistical Elaboration Model III. Non-quantitative Statistical Example IV. Quantitative Statistical Example Topics

2
I. The Definition of Causation Causation A. Co-variation B. Over a valid time frame C. Of a non-spurious nature D. That is grounded in theory - Four Characteristics

3
Causation II. The Statistical Elaboration Model A. Elimination B. Specification 1. Antecedent 2. Intervening Spuriousness X Y Z XY Z e.g. the effect of fire size (Z) on the relationship between # of firemen (X) and damage (Y) e.g. the effect of education (Z) on the relationship between age (X) and income (Y)

4
Causation III. Non-quantitative Statistical Example Step 1 – Construct the zero order cross-tabulation table. The Marginal (Zero-Order) Table MFTot Rep2515 40 Dem1525 40 Tot40 80 Step 2 – Calculate the zero order measure of association. e.g. Lambda = 40/40 – 30/40 =.25 or Phi = (25-20) 2 /20 + (15-20) 2 /20 + (15-20) 2 /20 + (25-20) 2 /20 = square root of 5/80 =.25

5
Causation Step 3 – Construct the first order partial tables. The Marginal Table M FTot Rep2515 40 Dem1525 40 Tot40 80 Step 4 – Calculate the partial measures of association. = M FTot Rep15 30 Dem15 30 Tot30 60 + M FTot Rep10 0 Dem 010 Tot10 20 Partial Table for YoungPartial Table for Old TotalYoungOld Lambda.25.001.00 Since the partials have changed from the marginal measure, one getting stronger and the other disappearing, we would say that we have specified the zero order relationship as probably intervening (i.e. we are born into a sex, grow older and as a result, join a political party). Step 5 – Form the conclusion

6
Causation IV. Quantitative Statistical Example Step 1 – Construct the zero order Pearsons correlations (r). Assume r xy =.55 where x = suicide rates and y = divorce rates. Assume further that r xz =.60 and r yz =.40, where z = unemployment rates. Step 2 – Calculate the partial correlation ( r xy.z ) ==.42 Step 3 – Draw conclusions ( r xy.z ) 2 =.18 (r xy ) 2 =.30 Therefore, Z accounts for (.30-.18) or 12% of Y and (.12/.30) or 40% of the relationship between X&Y.55 – (.6) (.4)

Similar presentations

OK

Measures of Association Quiz 1. What do phi and b (the slope) have in common? 2. Which measures of association are chi square based? 3. What do gamma,

Measures of Association Quiz 1. What do phi and b (the slope) have in common? 2. Which measures of association are chi square based? 3. What do gamma,

© 2018 SlidePlayer.com Inc.

All rights reserved.

To ensure the functioning of the site, we use **cookies**. We share information about your activities on the site with our partners and Google partners: social networks and companies engaged in advertising and web analytics. For more information, see the Privacy Policy and Google Privacy & Terms.
Your consent to our cookies if you continue to use this website.

Ads by Google

Free download ppt on autonomous car Ppt on atomic structure class 11 Ppt online form 2015 last date Ppt on tsunami warning system to mobile phones Ppt on class ab power amplifier Simple ppt on wifi technology Ppt on project life cycle Ppt on forward rate agreement calculation Ppt on teachers day images Ppt on bluetooth communication module