chrishaid
commented
9 years ago OK. So let's go with mapvizier. Now the question is capitalization:
- mapvizier
- mapVizier
- MAPvizier
- MAPVizier
I prefer all lowercase: easier to type, easier to remember. I basically hate packages where I have to require/library them 3-4 times because I can't remember if it is lowercase, CamelCase, snake_case, etc.
This is dated information, but I'm adding per Andrew's request so we don't lose the info.
More importantly, I just merged some new functions into the main branch:
dots(), an internal function to capture unevaluated dots arguments in a functionnwea_growth(), gets any or all NWEA norms using grade, start.rit, and measurementscale vectors. This usesdots()internally to ask for any of the norms (R22, S42, T12, etc.).kipp_quartile, calculates the foundation dumb quartile (or not! if you want it calculate real quartiles!) given a vector of percentiles. Returns a vector of integers or factors (your choice!)tiered_growth(), given a vector of quartile and another vector of grade levels, returns a vector of KIPP Tiered Growth factors/multiplierss2s_match(), given a long-format map assessments data.frame, and two season as a growth period, the functions creates two subsets by season in a given year and merges them with an inner join on on student id and measurement scale, then returns that data.frame with smartly labeled column for the second season in a pair. If you ask nicely will also calculate typical growth, typical growth targets, and a typical growth met/exceeded indicator. Ditto college ready growth, targets, and indicators. Though for these you'll need some properly named columns right now. Oh, ands2s_matchis super duper fast. Using the the three previous functions on the three years of long data and then using s2s join on each year for five (5!) "growth seasons" (f-s, s-s, f-w, w-s, f-f) and then binding all that up took like 1/2 a second. Seriously. That is totally rad.