dev/LIFIT.R
In timriffe/DemoTools: Standardize, Evaluate, and Adjust Demographic Data
# Author: tim
###############################################################################
# function design based on Computer programs for demographic analysis
# Eduardo Arriaga, Patricia Anderson, Larry Heligman.
# Washington : U.S. Dept. of Commerce, Bureau of the Census, International Statistical Programs
# Center, 1976.
#' mean absolute difference in survival rates
#'
#' @description Take two survival curves, use them to calculate 5-year survival
#' ratios, then take the mean absolute difference between these, with optional age trimming.
#' Based on LIFIT program from the MPCDA code base.
#'
#' @param lx1 numeric vector. The first survival function, any radix size
#' @param lx2 numeric vector. The second survival function, any radix size
#' @param Age1 integer vector. The age groups (lower bound) corresponding to \code{lx1}
#' @param Age2 integer vector. The age groups (lower bound) corresponding to \code{lx2}
#' @param ageMin integer. Optional lower age bound for calcs
#' @param ageMax integer. Optional upper age bound for calcs
#' @return the mean absolute difference in survival ratios
#' @export
#' @details \code{lx1} and \code{lx2} can be of different lengths, and needn't have identically
#' grouped data. For example, either or both input vectors could be in single or five-year age groups
#' for this function. Results are selected internally for 5-year age groups, and vector lengths are matched.
#' The input vectors can also be of different lifetable radices. As with the original Fortran code,
#' the open age group must be included in input vectors, even though it is not included in calcs.
#' If your final age group is not open, then tack an extra element to it to simulate an open element,
#' and just make sure to match ages.
#' @references
#' Eduardo Arriaga, Patricia Anderson, Larry Heligman (1976). Computer programs for demographic analysis
#' Washington : U.S. Dept. of Commerce, Bureau of the Census, International Statistical Programs
#' Center.
#'
#' @examples
#' lx1 <-c(1, 0.94265, 0.93344, 0.92708, 0.923, 0.92023, 0.91796, 0.91601,
#' 0.91431, 0.9128, 0.91145, 0.91025, 0.90914, 0.90805, 0.90692,
#' 0.90566, 0.90419, 0.90251, 0.90063, 0.89858, 0.89642, 0.89417,
#' 0.8918, 0.88923, 0.88647, 0.88356, 0.88046, 0.87721, 0.87386,
#' 0.87047, 0.86706, 0.8636, 0.86008, 0.85649, 0.85276, 0.84882,
#' 0.84465, 0.84027, 0.8357, 0.83102, 0.8264, 0.82193, 0.8175, 0.81296,
#' 0.80827, 0.80343, 0.79845, 0.79329, 0.78788, 0.78218, 0.77617,
#' 0.76982, 0.76309, 0.75596, 0.74837, 0.74029, 0.73182, 0.72307,
#' 0.71396, 0.70434, 0.69402, 0.68295, 0.67102, 0.6581, 0.64442,
#' 0.63012, 0.61486, 0.59811, 0.57943, 0.55896, 0.53739, 0.51528,
#' 0.49248, 0.46826, 0.44272, 0.41631, 0.38876, 0.36037, 0.33157,
#' 0.30217, 0.27334, 0.24599, 0.21948, 0.19412, 0.17029, 0.14826,
#' 0.12771, 0.10909, 0.09241, 0.07763, 0.0647, 0.05363, 0.04403,
#' 0.03578, 0.02877, 0.02289, 0.018, 0.01399, 0.01075, 0.00815,
#' 0.0061, 0.00451, 0.00329, 0.00236, 0.00168, 0.00117, 0.00081,
#' 0.00055, 0.00036, 0.00024, 0.00015)
#'lx2 <- c(1, 0.99361, 0.99315, 0.99284, 0.99264, 0.99246, 0.9923, 0.99216,
#' 0.99201, 0.99189, 0.99176, 0.99164, 0.99149, 0.99135, 0.99118,
#' 0.99096, 0.99069, 0.99033, 0.98993, 0.98946, 0.98902, 0.98857,
#' 0.98809, 0.98763, 0.98717, 0.98672, 0.98623, 0.98574, 0.98521,
#' 0.98468, 0.9841, 0.98351, 0.98285, 0.98213, 0.98134, 0.9805,
#' 0.97959, 0.9786, 0.97748, 0.97628, 0.97495, 0.97353, 0.97197,
#' 0.97032, 0.96847, 0.96655, 0.96443, 0.96225, 0.95984, 0.95724,
#' 0.95446, 0.95142, 0.94822, 0.94469, 0.94058, 0.93651, 0.93187,
#' 0.92678, 0.92112, 0.91508, 0.90846, 0.90128, 0.89336, 0.88466,
#' 0.87543, 0.86532, 0.85442, 0.84265, 0.82993, 0.81641, 0.80212,
#' 0.78656, 0.77024, 0.75237, 0.73333, 0.71304, 0.69102, 0.66797,
#' 0.64371, 0.61749, 0.58998, 0.55953, 0.52836, 0.49505, 0.46051,
#' 0.42472, 0.38756, 0.34995, 0.31203, 0.27485, 0.23825, 0.20292,
#' 0.16979, 0.13867, 0.11131, 0.08713, 0.06679, 0.04989, 0.03626,
#' 0.02561, 0.01755, 0.01165, 0.00749, 0.00466, 0.00281, 0.00163,
#' 0.00092, 5e-04, 0.00026, 0.00013, 7e-05)
#' ADM(lx1,lx2, 0:110)
#' ADM(lx1,lx2,0:110,ageMax = 80)
ADM <- function(
lx1,
lx2,
Age1,
Age2 = Age1,
ageMin = max(c(min(Age1),min(Age2))),
ageMax = min(c(max(Age1), max(Age2)))){
stopifnot(length(lx1) == length(Age1))
stopifnot(length(lx2) == length(Age2))
# remove open age group
n1 <- length(lx1)
n2 <- length(lx2)
lx1 <- lx1[-n1]
lx2 <- lx2[-n2]
Age1 <- Age1[-n1]
Age2 <- Age2[-n2]
# ages in common only
age5 <- AGEN(
Age1,
Age2,
N = 5,
consecutive = TRUE,
ageMin = ageMin,
ageMax = ageMax - 1)
# trim lx to needed ages
lx1_5 <- lx1[Age1 %in% age5]
lx2_5 <- lx2[Age2 %in% age5]
# survivor ratios
Sx1 <- ratx(lx1_5)
Sx2 <- ratx(lx2_5)
# absolute differences
AD <- Sx1 - Sx2
# mean absolute difference
mean(abs(AD))
}
#' mean absolute difference in age-ratios of survival rates
#'
#' @description Take two survival curves, use them to calculate 5-year survival
#' ratios, then again take the consecutive age-ratios of these. Finally, take the
#' mean absolute difference between ratios, with optional age trimming.
#' Based on LIFIT program from the MPCDA code base.
#'
#' @param lx1 numeric vector. The first survival function, any radix size
#' @param lx2 numeric vector. The second survival function, any radix size
#' @param Age1 integer vector. The age groups (lower bound) corresponding to \code{lx1}
#' @param Age2 integer vector. The age groups (lower bound) corresponding to \code{lx2}
#' @param ageMin integer. Optional lower age bound for calcs
#' @param ageMax integer. Optional upper age bound for calcs
#' @return the mean absolute difference in survival ratios
#' @export
#' @details \code{lx1} and \code{lx2} can be of different lengths, and needn't have identically
#' grouped data. For example, either or both input vectors could be in single or five-year age groups
#' for this function. Results are selected internally for 5-year age groups, and vector lengths are matched.
#' The input vectors can also be of different lifetable radices. As with the original Fortran code,
#' the open age group must be included in input vectors, even though it is not included in calcs.
#' If your final age group is not open, then tack an extra element to it to simulate an open element,
#' and just make sure to match ages.
#' @references
#' Eduardo Arriaga, Patricia Anderson, Larry Heligman (1976). Computer programs for demographic analysis
#' Washington : U.S. Dept. of Commerce, Bureau of the Census, International Statistical Programs
#' Center.
#' @examples
#' lx1 <-c(1, 0.94265, 0.93344, 0.92708, 0.923, 0.92023, 0.91796, 0.91601,
#' 0.91431, 0.9128, 0.91145, 0.91025, 0.90914, 0.90805, 0.90692,
#' 0.90566, 0.90419, 0.90251, 0.90063, 0.89858, 0.89642, 0.89417,
#' 0.8918, 0.88923, 0.88647, 0.88356, 0.88046, 0.87721, 0.87386,
#' 0.87047, 0.86706, 0.8636, 0.86008, 0.85649, 0.85276, 0.84882,
#' 0.84465, 0.84027, 0.8357, 0.83102, 0.8264, 0.82193, 0.8175, 0.81296,
#' 0.80827, 0.80343, 0.79845, 0.79329, 0.78788, 0.78218, 0.77617,
#' 0.76982, 0.76309, 0.75596, 0.74837, 0.74029, 0.73182, 0.72307,
#' 0.71396, 0.70434, 0.69402, 0.68295, 0.67102, 0.6581, 0.64442,
#' 0.63012, 0.61486, 0.59811, 0.57943, 0.55896, 0.53739, 0.51528,
#' 0.49248, 0.46826, 0.44272, 0.41631, 0.38876, 0.36037, 0.33157,
#' 0.30217, 0.27334, 0.24599, 0.21948, 0.19412, 0.17029, 0.14826,
#' 0.12771, 0.10909, 0.09241, 0.07763, 0.0647, 0.05363, 0.04403,
#' 0.03578, 0.02877, 0.02289, 0.018, 0.01399, 0.01075, 0.00815,
#' 0.0061, 0.00451, 0.00329, 0.00236, 0.00168, 0.00117, 0.00081,
#' 0.00055, 0.00036, 0.00024, 0.00015)
#'lx2 <- c(1, 0.99361, 0.99315, 0.99284, 0.99264, 0.99246, 0.9923, 0.99216,
#' 0.99201, 0.99189, 0.99176, 0.99164, 0.99149, 0.99135, 0.99118,
#' 0.99096, 0.99069, 0.99033, 0.98993, 0.98946, 0.98902, 0.98857,
#' 0.98809, 0.98763, 0.98717, 0.98672, 0.98623, 0.98574, 0.98521,
#' 0.98468, 0.9841, 0.98351, 0.98285, 0.98213, 0.98134, 0.9805,
#' 0.97959, 0.9786, 0.97748, 0.97628, 0.97495, 0.97353, 0.97197,
#' 0.97032, 0.96847, 0.96655, 0.96443, 0.96225, 0.95984, 0.95724,
#' 0.95446, 0.95142, 0.94822, 0.94469, 0.94058, 0.93651, 0.93187,
#' 0.92678, 0.92112, 0.91508, 0.90846, 0.90128, 0.89336, 0.88466,
#' 0.87543, 0.86532, 0.85442, 0.84265, 0.82993, 0.81641, 0.80212,
#' 0.78656, 0.77024, 0.75237, 0.73333, 0.71304, 0.69102, 0.66797,
#' 0.64371, 0.61749, 0.58998, 0.55953, 0.52836, 0.49505, 0.46051,
#' 0.42472, 0.38756, 0.34995, 0.31203, 0.27485, 0.23825, 0.20292,
#' 0.16979, 0.13867, 0.11131, 0.08713, 0.06679, 0.04989, 0.03626,
#' 0.02561, 0.01755, 0.01165, 0.00749, 0.00466, 0.00281, 0.00163,
#' 0.00092, 5e-04, 0.00026, 0.00013, 7e-05)
#' RDM(lx1, lx2, 0:110)
#' RDM(lx1, lx2, 0:110, ageMax = 80)
RDM <- function(
lx1,
lx2,
Age1,
Age2 = Age1,
ageMin = max(c(min(Age1),min(Age2))),
ageMax = min(c(max(Age1), max(Age2)))){
stopifnot(length(lx1) == length(Age1))
stopifnot(length(lx2) == length(Age2))
# remove open age group
n1 <- length(lx1)
n2 <- length(lx2)
lx1 <- lx1[-n1]
lx2 <- lx2[-n2]
Age1 <- Age1[-n1]
Age2 <- Age2[-n2]
# ages in common only
age5 <- AGEN(
Age1,
Age2,
N = 5,
consecutive = TRUE,
ageMin = ageMin,
ageMax = ageMax)
# select only needed lx
lx1_5 <- lx1[Age1 %in% age5]
lx2_5 <- lx2[Age2 %in% age5]
# survivor ratios
Sx1 <- ratx(lx1_5)
Sx2 <- ratx(lx2_5)
# ratios of the ratios
Rx1 <- ratx(Sx1)
Rx2 <- ratx(Sx2)
# differences of ratio ratios
RD <- Rx1 - Rx2
# mean absolute difference
mean(abs(RD))
}
timriffe/DemoTools documentation built on Oct. 14, 2024, 12:53 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# Author: tim
###############################################################################
# function design based on Computer programs for demographic analysis
# Eduardo Arriaga, Patricia Anderson, Larry Heligman.
# Washington : U.S. Dept. of Commerce, Bureau of the Census, International Statistical Programs
# Center, 1976.
#' mean absolute difference in survival rates
#'
#' @description Take two survival curves, use them to calculate 5-year survival
#' ratios, then take the mean absolute difference between these, with optional age trimming.
#' Based on LIFIT program from the MPCDA code base.
#'
#' @param lx1 numeric vector. The first survival function, any radix size
#' @param lx2 numeric vector. The second survival function, any radix size
#' @param Age1 integer vector. The age groups (lower bound) corresponding to \code{lx1}
#' @param Age2 integer vector. The age groups (lower bound) corresponding to \code{lx2}
#' @param ageMin integer. Optional lower age bound for calcs
#' @param ageMax integer. Optional upper age bound for calcs
#' @return the mean absolute difference in survival ratios
#' @export
#' @details \code{lx1} and \code{lx2} can be of different lengths, and needn't have identically
#' grouped data. For example, either or both input vectors could be in single or five-year age groups
#' for this function. Results are selected internally for 5-year age groups, and vector lengths are matched.
#' The input vectors can also be of different lifetable radices. As with the original Fortran code,
#' the open age group must be included in input vectors, even though it is not included in calcs.
#' If your final age group is not open, then tack an extra element to it to simulate an open element,
#' and just make sure to match ages.
#' @references
#' Eduardo Arriaga, Patricia Anderson, Larry Heligman (1976). Computer programs for demographic analysis
#' Washington : U.S. Dept. of Commerce, Bureau of the Census, International Statistical Programs
#' Center.
#'
#' @examples
#' lx1 <-c(1, 0.94265, 0.93344, 0.92708, 0.923, 0.92023, 0.91796, 0.91601,
#' 0.91431, 0.9128, 0.91145, 0.91025, 0.90914, 0.90805, 0.90692,
#' 0.90566, 0.90419, 0.90251, 0.90063, 0.89858, 0.89642, 0.89417,
#' 0.8918, 0.88923, 0.88647, 0.88356, 0.88046, 0.87721, 0.87386,
#' 0.87047, 0.86706, 0.8636, 0.86008, 0.85649, 0.85276, 0.84882,
#' 0.84465, 0.84027, 0.8357, 0.83102, 0.8264, 0.82193, 0.8175, 0.81296,
#' 0.80827, 0.80343, 0.79845, 0.79329, 0.78788, 0.78218, 0.77617,
#' 0.76982, 0.76309, 0.75596, 0.74837, 0.74029, 0.73182, 0.72307,
#' 0.71396, 0.70434, 0.69402, 0.68295, 0.67102, 0.6581, 0.64442,
#' 0.63012, 0.61486, 0.59811, 0.57943, 0.55896, 0.53739, 0.51528,
#' 0.49248, 0.46826, 0.44272, 0.41631, 0.38876, 0.36037, 0.33157,
#' 0.30217, 0.27334, 0.24599, 0.21948, 0.19412, 0.17029, 0.14826,
#' 0.12771, 0.10909, 0.09241, 0.07763, 0.0647, 0.05363, 0.04403,
#' 0.03578, 0.02877, 0.02289, 0.018, 0.01399, 0.01075, 0.00815,
#' 0.0061, 0.00451, 0.00329, 0.00236, 0.00168, 0.00117, 0.00081,
#' 0.00055, 0.00036, 0.00024, 0.00015)
#'lx2 <- c(1, 0.99361, 0.99315, 0.99284, 0.99264, 0.99246, 0.9923, 0.99216,
#' 0.99201, 0.99189, 0.99176, 0.99164, 0.99149, 0.99135, 0.99118,
#' 0.99096, 0.99069, 0.99033, 0.98993, 0.98946, 0.98902, 0.98857,
#' 0.98809, 0.98763, 0.98717, 0.98672, 0.98623, 0.98574, 0.98521,
#' 0.98468, 0.9841, 0.98351, 0.98285, 0.98213, 0.98134, 0.9805,
#' 0.97959, 0.9786, 0.97748, 0.97628, 0.97495, 0.97353, 0.97197,
#' 0.97032, 0.96847, 0.96655, 0.96443, 0.96225, 0.95984, 0.95724,
#' 0.95446, 0.95142, 0.94822, 0.94469, 0.94058, 0.93651, 0.93187,
#' 0.92678, 0.92112, 0.91508, 0.90846, 0.90128, 0.89336, 0.88466,
#' 0.87543, 0.86532, 0.85442, 0.84265, 0.82993, 0.81641, 0.80212,
#' 0.78656, 0.77024, 0.75237, 0.73333, 0.71304, 0.69102, 0.66797,
#' 0.64371, 0.61749, 0.58998, 0.55953, 0.52836, 0.49505, 0.46051,
#' 0.42472, 0.38756, 0.34995, 0.31203, 0.27485, 0.23825, 0.20292,
#' 0.16979, 0.13867, 0.11131, 0.08713, 0.06679, 0.04989, 0.03626,
#' 0.02561, 0.01755, 0.01165, 0.00749, 0.00466, 0.00281, 0.00163,
#' 0.00092, 5e-04, 0.00026, 0.00013, 7e-05)
#' ADM(lx1,lx2, 0:110)
#' ADM(lx1,lx2,0:110,ageMax = 80)
ADM <- function(
lx1,
lx2,
Age1,
Age2 = Age1,
ageMin = max(c(min(Age1),min(Age2))),
ageMax = min(c(max(Age1), max(Age2)))){
stopifnot(length(lx1) == length(Age1))
stopifnot(length(lx2) == length(Age2))
# remove open age group
n1 <- length(lx1)
n2 <- length(lx2)
lx1 <- lx1[-n1]
lx2 <- lx2[-n2]
Age1 <- Age1[-n1]
Age2 <- Age2[-n2]
# ages in common only
age5 <- AGEN(
Age1,
Age2,
N = 5,
consecutive = TRUE,
ageMin = ageMin,
ageMax = ageMax - 1)
# trim lx to needed ages
lx1_5 <- lx1[Age1 %in% age5]
lx2_5 <- lx2[Age2 %in% age5]
# survivor ratios
Sx1 <- ratx(lx1_5)
Sx2 <- ratx(lx2_5)
# absolute differences
AD <- Sx1 - Sx2
# mean absolute difference
mean(abs(AD))
}
#' mean absolute difference in age-ratios of survival rates
#'
#' @description Take two survival curves, use them to calculate 5-year survival
#' ratios, then again take the consecutive age-ratios of these. Finally, take the
#' mean absolute difference between ratios, with optional age trimming.
#' Based on LIFIT program from the MPCDA code base.
#'
#' @param lx1 numeric vector. The first survival function, any radix size
#' @param lx2 numeric vector. The second survival function, any radix size
#' @param Age1 integer vector. The age groups (lower bound) corresponding to \code{lx1}
#' @param Age2 integer vector. The age groups (lower bound) corresponding to \code{lx2}
#' @param ageMin integer. Optional lower age bound for calcs
#' @param ageMax integer. Optional upper age bound for calcs
#' @return the mean absolute difference in survival ratios
#' @export
#' @details \code{lx1} and \code{lx2} can be of different lengths, and needn't have identically
#' grouped data. For example, either or both input vectors could be in single or five-year age groups
#' for this function. Results are selected internally for 5-year age groups, and vector lengths are matched.
#' The input vectors can also be of different lifetable radices. As with the original Fortran code,
#' the open age group must be included in input vectors, even though it is not included in calcs.
#' If your final age group is not open, then tack an extra element to it to simulate an open element,
#' and just make sure to match ages.
#' @references
#' Eduardo Arriaga, Patricia Anderson, Larry Heligman (1976). Computer programs for demographic analysis
#' Washington : U.S. Dept. of Commerce, Bureau of the Census, International Statistical Programs
#' Center.
#' @examples
#' lx1 <-c(1, 0.94265, 0.93344, 0.92708, 0.923, 0.92023, 0.91796, 0.91601,
#' 0.91431, 0.9128, 0.91145, 0.91025, 0.90914, 0.90805, 0.90692,
#' 0.90566, 0.90419, 0.90251, 0.90063, 0.89858, 0.89642, 0.89417,
#' 0.8918, 0.88923, 0.88647, 0.88356, 0.88046, 0.87721, 0.87386,
#' 0.87047, 0.86706, 0.8636, 0.86008, 0.85649, 0.85276, 0.84882,
#' 0.84465, 0.84027, 0.8357, 0.83102, 0.8264, 0.82193, 0.8175, 0.81296,
#' 0.80827, 0.80343, 0.79845, 0.79329, 0.78788, 0.78218, 0.77617,
#' 0.76982, 0.76309, 0.75596, 0.74837, 0.74029, 0.73182, 0.72307,
#' 0.71396, 0.70434, 0.69402, 0.68295, 0.67102, 0.6581, 0.64442,
#' 0.63012, 0.61486, 0.59811, 0.57943, 0.55896, 0.53739, 0.51528,
#' 0.49248, 0.46826, 0.44272, 0.41631, 0.38876, 0.36037, 0.33157,
#' 0.30217, 0.27334, 0.24599, 0.21948, 0.19412, 0.17029, 0.14826,
#' 0.12771, 0.10909, 0.09241, 0.07763, 0.0647, 0.05363, 0.04403,
#' 0.03578, 0.02877, 0.02289, 0.018, 0.01399, 0.01075, 0.00815,
#' 0.0061, 0.00451, 0.00329, 0.00236, 0.00168, 0.00117, 0.00081,
#' 0.00055, 0.00036, 0.00024, 0.00015)
#'lx2 <- c(1, 0.99361, 0.99315, 0.99284, 0.99264, 0.99246, 0.9923, 0.99216,
#' 0.99201, 0.99189, 0.99176, 0.99164, 0.99149, 0.99135, 0.99118,
#' 0.99096, 0.99069, 0.99033, 0.98993, 0.98946, 0.98902, 0.98857,
#' 0.98809, 0.98763, 0.98717, 0.98672, 0.98623, 0.98574, 0.98521,
#' 0.98468, 0.9841, 0.98351, 0.98285, 0.98213, 0.98134, 0.9805,
#' 0.97959, 0.9786, 0.97748, 0.97628, 0.97495, 0.97353, 0.97197,
#' 0.97032, 0.96847, 0.96655, 0.96443, 0.96225, 0.95984, 0.95724,
#' 0.95446, 0.95142, 0.94822, 0.94469, 0.94058, 0.93651, 0.93187,
#' 0.92678, 0.92112, 0.91508, 0.90846, 0.90128, 0.89336, 0.88466,
#' 0.87543, 0.86532, 0.85442, 0.84265, 0.82993, 0.81641, 0.80212,
#' 0.78656, 0.77024, 0.75237, 0.73333, 0.71304, 0.69102, 0.66797,
#' 0.64371, 0.61749, 0.58998, 0.55953, 0.52836, 0.49505, 0.46051,
#' 0.42472, 0.38756, 0.34995, 0.31203, 0.27485, 0.23825, 0.20292,
#' 0.16979, 0.13867, 0.11131, 0.08713, 0.06679, 0.04989, 0.03626,
#' 0.02561, 0.01755, 0.01165, 0.00749, 0.00466, 0.00281, 0.00163,
#' 0.00092, 5e-04, 0.00026, 0.00013, 7e-05)
#' RDM(lx1, lx2, 0:110)
#' RDM(lx1, lx2, 0:110, ageMax = 80)
RDM <- function(
lx1,
lx2,
Age1,
Age2 = Age1,
ageMin = max(c(min(Age1),min(Age2))),
ageMax = min(c(max(Age1), max(Age2)))){
stopifnot(length(lx1) == length(Age1))
stopifnot(length(lx2) == length(Age2))
# remove open age group
n1 <- length(lx1)
n2 <- length(lx2)
lx1 <- lx1[-n1]
lx2 <- lx2[-n2]
Age1 <- Age1[-n1]
Age2 <- Age2[-n2]
# ages in common only
age5 <- AGEN(
Age1,
Age2,
N = 5,
consecutive = TRUE,
ageMin = ageMin,
ageMax = ageMax)
# select only needed lx
lx1_5 <- lx1[Age1 %in% age5]
lx2_5 <- lx2[Age2 %in% age5]
# survivor ratios
Sx1 <- ratx(lx1_5)
Sx2 <- ratx(lx2_5)
# ratios of the ratios
Rx1 <- ratx(Sx1)
Rx2 <- ratx(Sx2)
# differences of ratio ratios
RD <- Rx1 - Rx2
# mean absolute difference
mean(abs(RD))
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.