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Stata Journals 2013 Volume 13 No.2.pdf
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Articles and Columns 221
Maximum likelihood and generalized spatial two-stage least-squares estimators for
a spatial-autoregressive model with spatial-autoregressive disturbances . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . .D. M. Drukker, I. R. Prucha, and R. Raciborski 221
Creating and managing spatial-weighting matrices with the spmat command. . . .
. . . . . . . . . . . . . . . . . . . D. M. Drukker, H. Peng, I. R. Prucha, and R. Raciborski 242
A command for estimating spatial-autoregressive models with spatial-autoregressive
disturbances and additional endogenous variables . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . .D. M. Drukker, I. R. Prucha, and R. Raciborski 287
A command for Laplace regression . . . . . . . . . . . . . . . . . . . . . M. Bottai and N. Orsini 302
Importing U.S. exchange rate data from the Federal Reserve and standardizing
country names across datasets . . . . . . . . .B. Dicle, J. Levendis, and M. F. Dicle 315
Generating Manhattan plots in Stata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .D. E. Cook, K. R. Ryckman, and J. C. Murray 323
Semiparametric fixed-effects estimator . . . . . . . . . . . . . . . . . F. Libois and V. Verardi 329
Exact Wilcoxon signed-rank and Wilcoxon Mann–Whitney ranksum tests . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .T. Harris and J. W. Hardin 337
Extending the flexible parametric survival model for competing risks. . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. R. Hinchliffe and P. C. Lambert 344
Goodness-of-fit tests for categorical data . . . . . . . . . . . . . . R. Bellocco and S. Algeri 356
Standardizing anthropometric measures in children and adolescents with functions
for egen: Update . . . . . . . . . . . . . . . . . . . . . . . S. I. Vidmar, T. J. Cole, and H. Pan 366
Bonferroni and Holm approximations for ˇSid′ak and Holland–Copenhaver q-values
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .R. B. Newson 379
Fitting the generalized multinomial logit model in Stata . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Y. Gu, A. R. Hole, and S. Knox 382
Speaking Stata: Creating and varying box plots: Correction. . . . . . . . . . .N. J. Cox 398
Notes and Comments 401
Stata tip 115: How to properly estimate the multinomial probit model with heteroskedastic
errors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .M. Herrmann 401
Software Updates 406
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