| scan_stat | R Documentation | 
scan_stat calculates the spatial scan statistic
for a zone (a set of spatial regions).  The statistic is
the log of the likelihood ratio test statistic of the
chosen distribution.  If type = "poisson" and
a is more than zero, this statistic is penalized.
See references.
scan_stat(
  yin,
  ein = NULL,
  eout = NULL,
  ty,
  type = "poisson",
  popin = NULL,
  tpop = NULL,
  a = 0,
  shape = 1,
  yout = NULL,
  popout = NULL
)
stat_poisson(yin, yout, ein, eout, a = 0, shape = 1)
stat_binom(yin, yout, ty, popin, popout, tpop)
yin | 
 The total number of cases in the zone.  | 
ein | 
 The expected number of cases in the zone. Conventionally, this is the estimated overall disease risk across the study area, multiplied by the total population size of the zone.  | 
eout | 
 The expected number of cases outside the
zone.  This should be   | 
ty | 
 The total number of cases in the study area.  | 
type | 
 The type of scan statistic to implement. The
default choice are   | 
popin | 
 The total population in the zone.  | 
tpop | 
 The total population in the study area.  | 
a | 
 A tuning parameter for the adjusted log-likelihood ratio. See details.  | 
shape | 
 The shape of the ellipse, which is the ratio of the length of the longest and shortest axes of the ellipse. The default is 1, meaning it is a circle.  | 
yout | 
 The observed number of cases outside the
zone.  This should be   | 
popout | 
 The population outside the zone.  This
should be   | 
A vector of scan statistics.
Joshua French
Poisson scan statistic: Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics - Theory and Methods, 26(6): 1481-1496, <doi:10.1080/03610929708831995>
Penalized Poisson scan statistic: Kulldorff, M., Huang, L., Pickle, L. and Duczmal, L. (2006) An elliptic spatial scan statistic. Statistics in Medicine, 25:3929-3943. <doi:10.1002/sim.2490>
Binomial scan statistic: Duczmal, L. and Assuncao, R. (2004) A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters. Computational Statistics & Data Analysis, 45(2):269-286. <doi:10.1016/S0167-9473(02)00302-X>
# New York leukemia data
# total cases
ty <- 552
# total population
tpop <- 1057673
# poisson example with yin = 106 and ein = 62.13
scan_stat(yin = 106, ty = ty, ein = 62.13)
stat_poisson(
  yin = 106, yout = 552 - 106,
  ein = 62.13, eout = 552 - 62.13
)
# binomial example with yin = 41 and popin = 38999
scan_stat(
  yin = 41, ty = ty,
  popin = 38999, tpop = tpop, type = "binomial"
)
stat_binom(41, ty - 41, ty, 38999, tpop - 38999, tpop)
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