s2s_match: Merge two different assessment seasons (by student and...
In almartin82/MAP-visuals: KIPP MAP Visuals

Description Usage Arguments Details Value Examples

s2s_match a dataframe with two season results matched on student-measurement scale basis.

1 2	s2s_match(.data, season1 = "Fall", season2 = "Spring", sy = 2013, typical.growth = TRUE, college.ready = FALSE)

`.data`	a data frame with assessment data, in long-format (i.e., one student-assessment per row).
`season1`	a string of either "Fall", "Winter", or "Spring" for the first assessment season by which to subset `.data` and join on.
`season2`	a string of either "Fall", "Winter", or "Spring" for the first assessment season by which to subset `.data` and join on. Note that if "Spring" to "Fall" is a valid combination but norms cannot be calcualted for it.
`sy`	an integer indicating the (second half school year. For example, enter 2014 for the 2013-2104 school year. For assessment combinations that are ambiguious like spring to spring, the school year is taken to be the the school year for season 2 and season 1 is taken from the prior year.
`typical.growth`	boolean indicating if typical growth, typical growth target, and typical growth met/exceeded inditor are to be calculted. Requires that `.data` have norm columns.
`college.ready`	boolean indicating if college ready growth, college ready growth target, and college ready growth met/exceeded inditor are to be calculted. Requires that `.data` have KIPPTieredGrowth column.

This function returns a data frame that results from subsetting a long-format data MAP assessment data frame (i.e., where every students' test event occupies a single row), .data into two seasons and then mergeing the two subsets with an inner join on student id and measurement scale (via dplyr::inner_join) for the school year and seasons passed to it. All columns of .data are replicated, save of student id and measuremen scale (since these are used to merge on) with the later season's column names indicated wiht .2 suffix (i.e., TestRITScore.2).

If indicated (by setting the values of the typical.growth and college.ready parameters to TRUE) the function will also calculate the amount of growth (i.e. number of RIT points) and growth target (i.e., RIT score to attain) college ready growth.

Note well that for typical.growth=TRUE the original data frame, .data, must have reported norms for the requried growth season. The reported norm column must be named using the 2011 NWEA Norms table convention of the season (winter through fall) indicated by corresponding integers (1-4); For example fall to spring requires .data has a field names R42 and spring to spring wourld be R22. These columns can be easily added to a CDF by using the nwea_growth function.

Also note that calculating college ready growth and growth targets requires that .data has a column named KIPPTieredGrowth containing a KIPP tiered multiplier for each student-assessment. These data can be generated using the tiered_growth function.

a data.frame ith at least 2(m-1) columns (and as many as $(m-1) + 6) and a row for every student-assessment that occured in both season 1 and season 2.