View source: R/posthoc_Trends_vsRef.R
posthoc_Trends_vsRef | R Documentation |
This function is a wrapper based on emmeans
, and needs a ordinary linear model produced by simple_model
or a mixed effects model produced by mixed_model
or mixed_model_slopes
(or generated directly with lm
, lme4
or lmerTest
calls). At least one of the factors should be a numeric covariate whose slopes you wish to find. It also needs to know the fixed factor(s), which should match those in the model and data table.
posthoc_Trends_vsRef(
Model,
Fixed_Factor,
Trend_Factor,
Ref_Level = 1,
P_Adj = "sidak",
...
)
Model |
a model object fit using |
Fixed_Factor |
one or more categorical variables, provided as a vector (see Examples), whose levels you wish to compare pairwise. Names of Fixed_Factor should match Fixed_Factor used to fit the model. When more than one factor is provided e.g. |
Trend_Factor |
a quantitative variable that interacts with a factor and whose slope (trend) is to be compared |
Ref_Level |
the level within that factor to be considered the reference or control to compare other levels to (to be provided as a number - by default R orders levels alphabetically); default |
P_Adj |
method for correcting P values for multiple comparisons. Default is "sidak", can be changed to "bonferroni". See Interaction analysis in emmeans in the manual for |
... |
additional arguments for |
Checkout the Interactions with covariates section in the emmeans vignette for more details. One of the independent variables should be a quantitative (e.g. time points) variable whose slope (trend) you want to find at levels of the other factor.
returns an "emm_list" object containing slopes and their contrasts calculated through emtrends
.
#create an lm model
#Time2 is numeric (time points)
m1 <- simple_model(data = data_2w_Tdeath,
Y_value = "PI", Fixed_Factor = c("Genotype", "Time2"))
posthoc_Trends_vsRef(Model = m1,
Fixed_Factor = "Genotype",
Trend_Factor = "Time2",
Ref_Level = 2)
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