MIGRATION THROUGH SURNAMES IN CAMPOBASSO PROVINCE, ITALY

2001 ◽  
Vol 33 (2) ◽  
pp. 305-310 ◽  
Author(s):  
G. BIONDI ◽  
P. RASPE ◽  
C. G. N. MASCIE-TAYLOR

Data on grandparental surnames were obtained from schoolchildren in 22 communes from Campobasso Province, Italy (Molise Region). The distribution of surnames was shown to be almost exactly linear by a log2–log2 transformation, which justified the fitting of the data to Fisher’s logarithmic distribution. The values for ν were higher among women. When ν was standardized to minimize bias due to sample size, the value was one-third the estimate of migration from exogamy data. The higher values of ν for females indicate that there is greater mobility of female marriage partners than males.

2005 ◽  
Vol 112 (1) ◽  
pp. 268-279 ◽  
Author(s):  
Richard B. Anderson ◽  
Michael E. Doherty ◽  
Neil D. Berg ◽  
Jeff C. Friedrich
Keyword(s):  

2011 ◽  
Author(s):  
M. Lopez-Ramon ◽  
C. Castro ◽  
J. Roca ◽  
J. Lupianez

2009 ◽  
Author(s):  
Dennis L. Jackson ◽  
Marc Frey ◽  
Jennifer Voth
Keyword(s):  

2007 ◽  
Author(s):  
Natalie A. Obrecht ◽  
Gretchen B. Chapman ◽  
Rochel Gelman

1990 ◽  
Vol 29 (03) ◽  
pp. 243-246 ◽  
Author(s):  
M. A. A. Moussa

AbstractVarious approaches are considered for adjustment of clinical trial size for patient noncompliance. Such approaches either model the effect of noncompliance through comparison of two survival distributions or two simple proportions. Models that allow for variation of noncompliance and event rates between time intervals are also considered. The approach that models the noncompliance adjustment on the basis of survival functions is conservative and hence requires larger sample size. The model to be selected for noncompliance adjustment depends upon available estimates of noncompliance and event rate patterns.


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