English (US) |
Cambridge |
Cambridge University Press |
625 |
9780521686891, 052168689X, 0521867061, 9780521867061 |
Published - 2007 |
Analytical methods for social research |
- Modèles multiniveaux (Statistique)
- Regressieanalyse
- data analysis
- Multiniveau-analyse
- Matematisk statistik
- Analyse de régression
- Statistics as Topic
- Regression analysis
- Analyse statistique
- Multilevel models (Statistics)
- Regressionsanalys
- Análise de regressão e de correlação
- Multivariat analys
- Méthodes statistiques
- Regressionsanalyse
- statistical methods
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS
SHOWING 1-8 OF 8 REFERENCES
Scaling regression inputs by dividing by two standard deviations
- A. Gelman
Mathematics
Statistics in medicine
- 2008
This work recommends rescaling as a default option--an improvement upon the usual approach of including variables in whatever way they are coded in the data file--so that the magnitudes of coefficients can be directly compared as a matter of routine statistical practice.
how to present this material to students
how to present this material to students
Logistic regression u.data <-cbind (1:J, u) dimnames(u.data)[[2]] <-c("group
Logistic regression u.data <-cbind (1:J, u) dimnames(u.data)[[2]] <-c("group
sigma.hat(M1.sim))
sigma.hat(M1.sim))
Causal Effects in NonExperimental Studies : Re - Evaluating the Evaluation of Training Programs
Journal of the American Statistical Association
- 1999
See Also display, lm, glm, lmer Examples #Examples of "sim" set.seed (1) J <-15 n <-J * (J+1)/2 group <-rep (1:J, 1:J) References
See Also display, lm, glm, lmer Examples #Examples of "sim" set.seed (1) J <-15 n <-J * (J+1)/2 group <-rep (1:J, 1:J) References
M1.sim)) # Logistic regression u.data <-cbind (1:J, u) dimnames(u.data)[[2]] <-c("group
quantile(sigma.hat
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