commuteanova: Find out if times differ significantly
In Statgnome/commuteconvergence: Compare Commute Times using Google Sheets

Description Usage Arguments Details Value Note Author(s)

Takes a data frame of times in minutes, as integers, which have a variable, Day, defining their factor group, and returns the conclusion of an ANOVA.

1 2	commuteanova(commutedf,Leave="Left",Arrive="ArriveDesk", Time="Total",Group="Day",usertimebins=6)

`commutedf`	Data frame which must contain either two columns Arrive and Leave, or one column, Total. Total contains an integer value in minutes for a total commute time. Arrive and Leave must contain time of arrival at destination and time of departure from residence, respectively. All other arguments are optional, and all arguments, accept for commutedf itself, have defaults. Leave, Arrive, Time, and Group all have default character strings for column names in commutedf, and timebins has a default of 6. Timebins is how many different groups into which the commuting window will be split for analysis.
`Leave`	Time of departure column name. Default: "Left"
`Arrive`	Time of arrival column name. Default: "ArriveDesk"
`Time`	Total commute time column name. Default: "Total"
`Group`	Group name for analysis by factor. Default: "Day"
`usertimebins`	Integer for number of groups to split times into for k-means clustering. Default: 6.

Perhaps this can be generalized to other time collection purposes.

The returned message advises whether the times are significantly different by Day, and if not it will still advise which day has the shortest average time, or commute.

wubba lubba dub dub

David Burton, URMC Dept. of Biostatistics

Statgnome/commuteconvergence documentation built on May 28, 2019, 3:16 p.m.