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MOMOpack for R

News

MOMO 2020.9.3

Spring weeks of 2020, COVID-19, permanently excluded from baseline estimation

MOMO 2020.4.17

Ydrop and Wdrop as parameters glmnet removed from list of dependencies

MOMO 2018.8.24

  • There are now more options for extracting data from inside your MoMo run. Previously only MOMO::dataExport$toSave was available, however, now there is also MOMO::dataExport$aggr, MOMO::dataExport$aggr_fullDelay, and MOMO::dataExport$aggr_delay

MOMO 2018.8.23

  • The new delay correction that Jens developed in December 2017 is now available. This can be chosen by delayVersion="2017-12", or the original delay correction can be chosen by delayVersion="original" (default).

Initial: MOMO 2017.12.14

  • This is a full port of the Stata A-MOMO package to R. The code used to analyze mortality data for the EuroMOMO project.

How to install

Please use the drat repository to install this package from, as the drat repository only contains package versions that have passed testing.

install.packages("MOMO", repos = c("https://euromomonetwork.github.io/drat", "https://cran.rstudio.com"))

Basic example

SetOpts(
  DoA=as.Date("2013-12-31"),
  DoPR=as.Date("2008-1-1"),
  WStart=1,
  WEnd=52,
  country = "Denmark",
  source = "SSI",
  MFILE = "DoD_DoR.txt",
  HFILE = "holidays.txt",
  INPUTDIR = system.file("testdata", package="MOMO"),
  WDIR = tempdir(),
  back = 3,
  WWW = 290,
  Ysum = 2013,
  Wsum = 40,
  USEglm2 = TRUE,
  useAUTOMN = TRUE,
  datesISO = FALSE,
  plotGraphs = TRUE,
  delayVersion = "2017-12",
  MOMOgroups = list(`0to14` = "0 <= age & age <= 14",
                    `15to44` = "15 <= age & age <= 44",
                    `45to64` = "45 <= age & age <= 64",
                    `65P` = "age >= 65 & !is.na(age)",
                    `65to74` = "65 <= age & age <= 74",
                    `75to84` = "75 <= age & age <= 84",
                    `85P` = "age >= 85 & !is.na(age)",
                    `Total` = "age >= 0 | is.na(age)"
  ),
  MOMOmodels = c(`0to14` = "LINE",
                 `15to44` = "LINE_SIN",
                 `45to64` = "LINE_SIN",
                 `65P` = "LINE_SIN",
                 `65to74` = "LINE_SIN",
                 `75to84` = "LINE_SIN",
                 `85P` = "LINE_SIN",
                 `Total` = "LINE_SIN"
  ),
  Ydrop = 9999,
  Wdrop = 99,
  verbose = TRUE
)

RunMOMO()

Another example using MDATA and HDATA instead of MFILE and HFILE

MDATA <- as.data.frame(data.table::fread(file.path(system.file("testdata",package="MOMO"),"DoD_DoR.txt")))
HDATA <- as.data.frame(data.table::fread(file.path(system.file("testdata",package="MOMO"),"holidays.txt")))

SetOpts(
  DoA=as.Date("2013-12-31"),
  DoPR=as.Date("2008-1-1"),
  WStart=1,
  WEnd=52,
  country = "Denmark",
  source = "SSI",
  MDATA = MDATA,
  HDATA = HDATA,
  WDIR = tempdir(),
  back = 3,
  WWW = 290,
  Ysum = 2013,
  Wsum = 40,
  USEglm2 = TRUE,
  useAUTOMN = TRUE,
  datesISO = FALSE,
  plotGraphs = TRUE,
  delayVersion = "2017-12",
  MOMOgroups = list(`0to14` = "0 <= age & age <= 14",
                    `15to44` = "15 <= age & age <= 44",
                    `45to64` = "45 <= age & age <= 64",
                    `65P` = "age >= 65 & !is.na(age)",
                    `65to74` = "65 <= age & age <= 74",
                    `75to84` = "75 <= age & age <= 84",
                    `85P` = "age >= 85 & !is.na(age)",
                    `Total` = "age >= 0 | is.na(age)"
  ),
  MOMOmodels = c(`0to14` = "LINE",
                 `15to44` = "LINE_SIN",
                 `45to64` = "LINE_SIN",
                 `65P` = "LINE_SIN",
                 `65to74` = "LINE_SIN",
                 `75to84` = "LINE_SIN",
                 `85P` = "LINE_SIN",
                 `Total` = "LINE_SIN"
  ),
  Ydrop = 9999,
  Wdrop = 99,
  verbose = TRUE
)

RunMOMO()

Delay corrections available

Delay correction Description
original ???
sincos original+sin52+cos52
richard Interacts WR with categorical YoDi, includes closed, sin52, and cos52nb2 ~ WRXX*as.factor(YoDi) + closed + sin52 + cos52

original

???

sincos

???

richard

nb2 ~ WRXX*as.factor(YoDi) + closed + sin52 + cos52