Description Usage Arguments Details Value Author(s) Examples
Interfaces to aod
functions that can be used
in a pipeline implemented by magrittr
.
1 2 3 4 5 6 7 | ntbt_betabin(data, ...)
ntbt_donner(data, ...)
ntbt_negbin(data, ...)
ntbt_quasibin(data, ...)
ntbt_quasipois(data, ...)
ntbt_raoscott(data, ...)
ntbt_splitbin(data, ...)
|
data |
data frame, tibble, list, ... |
... |
Other arguments passed to the corresponding interfaced function. |
Interfaces call their corresponding interfaced function.
Object returned by interfaced function.
Roberto Bertolusso
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | ## Not run:
library(intubate)
library(magrittr)
library(aod)
## ntbt_betabin: beta-binomial generalized linear model accounting
## for overdispersion in clustered binomial data (n, y)
data(orob2)
## Original function to interface
betabin(cbind(y, n - y) ~ seed, ~ 1, data = orob2)
## The interface puts data as first parameter
ntbt_betabin(orob2, cbind(y, n - y) ~ seed, ~ 1)
## so it can be used easily in a pipeline.
orob2 %>%
ntbt_betabin(cbind(y, n - y) ~ seed, ~ 1)
## ntbt_donner: Test of Proportion Homogeneity using Donner's Adjustment
data(rats)
## Original function to interface
donner(formula = cbind(y, n - y) ~ group, data = rats)
## The interface puts data as first parameter
ntbt_donner(rats, formula = cbind(y, n - y) ~ group)
## so it can be used easily in a pipeline.
rats %>%
ntbt_donner(formula = cbind(y, n - y) ~ group)
## ntbt_negbin: negative-binomial log linear model accounting
## for overdispersion in counts y
data(salmonella)
## Original function to interface
negbin(y ~ log(dose + 10) + dose, ~ 1, salmonella)
## The interface puts data as first parameter
ntbt_negbin(salmonella, y ~ log(dose + 10) + dose, ~ 1)
## so it can be used easily in a pipeline.
salmonella %>%
ntbt_negbin(y ~ log(dose + 10) + dose, ~ 1)
## ntbt_quasibin: Quasi-Likelihood Model for Proportions
data(orob2)
## Original function to interface
quasibin(cbind(y, n - y) ~ seed * root, data = orob2, phi = 0)
## The interface puts data as first parameter
ntbt_quasibin(orob2, cbind(y, n - y) ~ seed * root, phi = 0)
## so it can be used easily in a pipeline.
orob2 %>%
ntbt_quasibin(cbind(y, n - y) ~ seed * root, phi = 0)
## ntbt_quasipois: Quasi-Likelihood Model for Counts
data(salmonella)
## Original function to interface
quasipois(y ~ log(dose + 10) + dose, data = salmonella)
## The interface puts data as first parameter
ntbt_quasipois(salmonella, y ~ log(dose + 10) + dose)
## so it can be used easily in a pipeline.
salmonella %>%
ntbt_quasipois(y ~ log(dose + 10) + dose)
## ntbt_raoscott: Test of Proportion Homogeneity using Rao and Scott's Adjustment
data(rats)
## Original function to interface
raoscott(cbind(y, n - y) ~ group, data = rats)
## The interface puts data as first parameter
ntbt_raoscott(rats, cbind(y, n - y) ~ group)
## so it can be used easily in a pipeline.
rats %>%
ntbt_raoscott(cbind(y, n - y) ~ group)
## ntbt_splitbin: Split Grouped Data Into Individual Data
mydata <- data.frame(
success = c(0, 1, 0, 1),
f1 = c("A", "A", "B", "B"),
f2 = c("C", "D", "C", "D"),
n = c(4, 2, 1, 3)
)
## Original function to interface
splitbin(formula = n ~ f1 + f2 + success, data = mydata)
## The interface puts data as first parameter
ntbt_splitbin(mydata, formula = n ~ f1 + f2 + success)
## so it can be used easily in a pipeline.
mydata %>%
ntbt_splitbin(formula = n ~ f1 + f2 + success)
## End(Not run)
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