version 0.9-0.0

DESCRIPTION

@@ -2,8 +2,8 @@ Package: SGP
 Type: Package
 Title: An R Package for the Calculation and Visualization of Student
         Growth Percentiles & Percentile Growth Trajectories.
-Version: 0.8-0.0
-Date: 2012-1-9
+Version: 0.9-0.0
+Date: 2012-4-12
 Authors@R: c(person("Damian", "Betebenner",
         email="dbetebenner@nciea.org", role=c("aut", "cre")),
         person("Adam", "Van Iwaarden",
@@ -14,23 +14,27 @@ Author: Damian W. Betebenner <dbetebenner@nciea.org>, Adam Van Iwaarden
         <ben.domingue@gmail.com> with contributions from Jonathan
         Weeks, John Stewart, Jinnie Choi, Xin Wei, and Hi Shin Shim.
         With special thanks to State Department of Education analysts:
-        Dr. Sarah Polasky (Arizona), Rebecca Gau (Arizona), Marie
-        Huchton (Colorado), Ayaka Nukui (Idaho), Dr. Carissa Miller
-        (Idaho), Dr. Wes Bruce (Indiana), Robert Hochsegang (Indiana),
-        Xuewen Sheng (Kansas), Robert Lee (Massachusetts), Ken Thompson
+        Dr. Sarah Polasky (Arizona), Rebecca Gau (Arizona), Dr. Bill
+        Bonk (Colorado), Marie Huchton (Colorado), Glenn Hirata
+        (Hawaii), Glenn Nochi (Hawaii), Ayaka Nukui (Idaho), Dr.
+        Carissa Miller (Idaho), Dr. Wes Bruce (Indiana), Robert
+        Hochsegang (Indiana), Xuewen Sheng (Kansas), Robert Lee
+        (Massachusetts), Joe DeCastra (Mississippi), Ken Thompson
         (Mississippi), Soo Yeon Cho (Missouri), Jeff Halsell (Nevada),
-        Selcuk Ozdemir (Nevada), Deb Wiswell (New Hampshire), Katya
-        Levitan-Reiner (New Haven Public Schools), Jessica Brown (Rhode
-        Island), Ana Karantonis (Rhode Island), Dr. Deborah Jonas
-        (Virginia), Juan D'Brot (West Virginia), Nate Hixson (West
-        Virginia), Justin Meyer (Wisconsin), Joseph Newton (Wisconsin),
-        Dr. Philip Olsen (Wisconsin), Nick Stroud (Wisconsin).
+        Selcuk Ozdemir (Nevada), Roger Silva (Nevada), Deb Wiswell (New
+        Hampshire), Katya Levitan-Reiner (New Haven Public Schools),
+        Jason Becker (Rhode Island), Jessica Brown (Rhode Island), Ana
+        Karantonis (Rhode Island), Dr. Deborah Jonas (Virginia), Juan
+        D'Brot (West Virginia), Nate Hixson (West Virginia), Daniel
+        Bush (Wisconsin), Justin Meyer (Wisconsin), Joseph Newton
+        (Wisconsin), Dr. Philip Olsen (Wisconsin), Nick Stroud
+        (Wisconsin).
 Maintainer: Damian W. Betebenner <dbetebenner@nciea.org>
-Depends: R (>= 2.12), boot, colorspace, data.table (>= 1.7.5), foreach,
-        grid, gridBase, methods, plyr, randomNames (>= 0.0-4),
-        quantreg, splines, SGPdata
-Suggests: doMC, doMPI, doSMP, doSNOW, doRedis, multicore, pdf2, sn,
-        snow
+Depends: R (>= 2.12), boot, colorspace, data.table (>= 1.7.9), foreach,
+        grid, gridBase, methods, plyr, reshape2, randomNames (>=
+        0.0-5), quantreg, splines, SGPdata
+Suggests: doMC, doMPI, doParallel, doRedis, doSNOW, multicore,
+        parallel, pdf2, RSQLite, sn, snow
 Description: Functions to calculate student growth percentiles and
         percentile growth projections/trajectories for students using
         large scale, longitudinal assessment data.  Functions use
@@ -48,6 +52,6 @@ URL: http://cran.r-project.org/web/packages/SGP/,
 LazyLoad: Yes
 LazyData: Yes
 License: CC BY-SA 3.0 US | CC BY-NC-SA 3.0 + file LICENSE
-Packaged: 2012-01-09 13:29:49 UTC; damian
+Packaged: 2012-04-12 13:57:02 UTC; damian
 Repository: CRAN
-Date/Publication: 2012-01-10 07:25:55
+Date/Publication: 2012-04-12 14:02:39

MD5

@@ -1,49 +1,55 @@
-e76ef1608f924b1003439a5bf28adc39 *DESCRIPTION
+f7d37be6c6051d51ab5dd8ceb6f65482 *DESCRIPTION
 6b502fc43fcb15060dbba9ef541a4153 *LICENSE
-3003712a10ed1f787235e11b1a9ad3ed *NAMESPACE
+04f4339b76e513e72482050b6e2073ad *NAMESPACE
 544ada155164636207236f46922df7e0 *R/SGP-class.R
-191456e498559660316bae85a6684d77 *R/abcSGP.R
-e0defcf10b893ec2794929c64cdfe0fe *R/analyzeSGP.R
+43fa686fcafd633f269893e919f623c2 *R/abcSGP.R
+e136e1f5c9451666a9e1b6b9abefadb8 *R/analyzeSGP.R
 baddb02b7b11493cf315dd01c27d24a7 *R/as.splineMatrix.R
-90b1e769c07c0f392d478d18423fc6bf *R/baselineSGP.R
-e68d620d75d22642fff67d379a41c8db *R/bubblePlot.R
-3ef5ff16515db7048972032152563dde *R/bubblePlot_Styles.R
-76625f81c9e880eeb191b4efab4284ed *R/combineSGP.R
-83ebf4b07c7ac077f383619b2a4b94ed *R/growthAchievementPlot.R
+a22d5ccd019c1ce1e1fb3f6042d08775 *R/baselineSGP.R
+7cb1710a2cc552c66a0fe778e254e30a *R/bubblePlot.R
+03de561abbd78a8d4b64622f28b57777 *R/bubblePlot_Styles.R
+cc9efc8aea55337e3c80326bb04a705f *R/capwords.R
+6560591a62812fe87250b8e010428fc1 *R/combineSGP.R
+62f98e360429f9645e7cf314f603fe3f *R/growthAchievementPlot.R
+81769c5c1e4a51714785786ab91701af *R/growthAchievementPlot_Styles.R
 3f9d12dd95adcad8e30e2247d49c9aac *R/is.SGP.R
 19cc4cce9ffb89ce7e1bce0fb43d4e46 *R/is.splineMatrix.R
-0da9c98914ce15391dcb6243298f819c *R/outputSGP.R
-b456722a6e31cfafa586c0182f910b63 *R/prepareSGP.R
+918501e75f01733880f3cdff00141b8a *R/outputSGP.R
+2f1ef13a07b88a570d7067d8a87cd12e *R/prepareSGP.R
 2fd8a080aee35af3d5deb00dc994232d *R/splineMatrix-class.R
-33caeefbf46c6555c97893989d453a3b *R/studentGrowthPercentiles.R
-16f3dea1fd87c8ae51b96532617c3474 *R/studentGrowthPlot.R
-8b929300faad0ecde4280435e0e7ea38 *R/studentGrowthPlot_Styles.R
-b3509ccd1ff167b0fafc9387d89f93b6 *R/studentGrowthProjections.R
-4104b05eb49efc58175f40740dc58027 *R/summarizeSGP.R
+e684eab6b331d23f3f8bdf6fc05dd557 *R/sqliteSGP.R
+9446ae9bbfbd0d73c69be7cceaaf9835 *R/startParallel.R
+e010c4a98c73e38ddb4ed56ad8d9ea48 *R/stopParallel.R
+db0acddd53e76c21a1cbbe1f7d4e2424 *R/studentGrowthPercentiles.R
+2c7c5a060aa79a616ceee28c8323923a *R/studentGrowthPlot.R
+23204e37a05e319ea04d74b30664707d *R/studentGrowthPlot_Styles.R
+bf0e8f1b37113b7ba87eb05753e9fb82 *R/studentGrowthProjections.R
+e4b35332ea499f687430c2157b084a52 *R/summarizeSGP.R
 184959e6bf8f6a00c0e84330c632b5d4 *R/viewSummaryGroups.R
-85e684d948e29e41d7c69136514014ec *R/visualizeSGP.R
-14e9d8fbfe6fd2e641feb21bce4df592 *data/SGPstateData.rda
+bd5b86ae7dadb966693059a6fca79765 *R/visualizeSGP.R
+260959027b2893860d1db9847fdb9bad *data/SGPstateData.rda
 3406f6148aa153daa87a96b2d8a2c0c6 *data/datalist
-62f17980440abfefc8a7138f8f1ec74a *inst/CITATION
-c791fc44b38f2ead242a130c6cfb474b *inst/NEWS
+94fd8a9a6322bd83752a3686189cd12b *inst/CITATION
+9d55128fa1cba4400f4a7e98e8c07d5d *inst/NEWS
 99ea0f9ec9684dddedfce27e4d440cee *inst/doc/sgpPrimer.pdf
 299c204e5e10d7ea4e579b8f70a1f4fd *man/SGP-class.Rd
-21bd63324990dd002f4966f01faf2aba *man/SGP-package.Rd
-8d7c7dfeeabf7681602c4d731f5acd5d *man/SGPstateData.Rd
-318848f84aec31b10f104d8f581cd703 *man/abcSGP.Rd
-95bab4e82832c6f558b8c84495677d9c *man/analyzeSGP.Rd
+0452d4c7fc71358e632ea269929f761c *man/SGP-package.Rd
+89fa82329963e4894dcc78d040129e7f *man/SGPstateData.Rd
+723328bbe674405efb90d158748b010a *man/abcSGP.Rd
+990bf43e2cbe328417efaa74bf0ef6a7 *man/analyzeSGP.Rd
 93345f1903c3084d4a6394218598d8f5 *man/baselineSGP.Rd
 eb74d5a4e06fbc3b903d04d01c16e24f *man/bubblePlot.Rd
-db26faee41f21dd283648020cbd142fb *man/bubblePlot_Styles.Rd
-44c0a6404d3c01c80851b6ab120d8381 *man/combineSGP.Rd
-22e3a47fae25e4c4349d3a3cb576434d *man/growthAchievementPlot.Rd
-71613b5d60ec02a951aa674e349b0452 *man/outputSGP.Rd
-cfea569ebc3bd9fe259200b2fd4a4839 *man/prepareSGP.Rd
+c9809e406f19b890c90c4581f618cc7a *man/bubblePlot_Styles.Rd
+0573fcb179cfb4d20d17d82965323577 *man/combineSGP.Rd
+7919330186f31296cb370913b6ff1db1 *man/growthAchievementPlot.Rd
+65b19d0f97c68afb043b33598f3e3308 *man/growthAchievementPlot_Styles.Rd
+712e70928f3aced631fc8e627ade37b3 *man/outputSGP.Rd
+3a8126fce5f93dfb9b5346cecac6d744 *man/prepareSGP.Rd
 f60ac782f891f7a52dda49aaf76c0be2 *man/splineMatrix-class.Rd
-db7e633f9763a08cccbcee1a8b8bfde7 *man/studentGrowthPercentiles.Rd
-136c2308a2d4b945dccc2b97dc22f232 *man/studentGrowthPlot.Rd
-1f7a4947de2e87aa5e7b9d4523c891a6 *man/studentGrowthPlot_Styles.Rd
-b404e31267ecbea971c7af4dc4b2ca87 *man/studentGrowthProjections.Rd
-6931146675e0dc5458c4f2d2d50bc238 *man/summarizeSGP.Rd
+4fa1f650ffdf47baa813396e25a9d9ba *man/studentGrowthPercentiles.Rd
+298beb66e82a03cb6cd7a8a7c0c0c3c8 *man/studentGrowthPlot.Rd
+ccd2d1a45d8d83372c52b9113746a5b8 *man/studentGrowthPlot_Styles.Rd
+4335e59ae3dfab4bbb47a721b30e6fc6 *man/studentGrowthProjections.Rd
+39c0b23ab16c8b2350db803ff039bc77 *man/summarizeSGP.Rd
 3e2c004c6b943c7fa1130d0a140acf3e *man/viewSummaryGroups.Rd
-6f74bb1ba0d8a2d7d3d7f007dfbe3982 *man/visualizeSGP.Rd
+e3885089d386e1424fc3fc9d5360da43 *man/visualizeSGP.Rd

NAMESPACE

@@ -2,6 +2,7 @@ import("data.table")
 import("foreach")
 import("grid")
 import("methods")
+import("reshape2")
 import("plyr")
 importFrom("splines", "bs")
 import(SGPdata)
@@ -15,6 +16,7 @@ export(
 	"bubblePlot_Styles",
 	"combineSGP",
 	"growthAchievementPlot",
+	"growthAchievementPlot_Styles",
 	"is.splineMatrix",
 	"is.SGP",
 	"outputSGP",

R/abcSGP.R

@@ -15,29 +15,10 @@ function(sgp_object,
 	simulate.sgps=TRUE,
 	parallel.config=NULL,
 	save.intermediate.results=FALSE,
-	sgp.summaries=list(MEDIAN_SGP="median_na(SGP)",
-		MEDIAN_SGP_TARGET="median_na(SGP_TARGET)",
-		PERCENT_CATCHING_UP_KEEPING_UP="percent_in_category(CATCH_UP_KEEP_UP_STATUS, list(c('Catch Up: Yes', 'Keep Up: Yes')), list(c('Catch Up: Yes', 'Catch Up: No', 'Keep Up: Yes', 'Keep Up: No')))",
-		MEDIAN_SGP_COUNT="num_non_missing(SGP)",
-		PERCENT_AT_ABOVE_PROFICIENT="percent_in_category(ACHIEVEMENT_LEVEL, list(c('Proficient', 'Advanced')), list(c('Unsatisfactory', 'Partially Proficient', 'Proficient', 'Advanced')))",
-		PERCENT_AT_ABOVE_PROFICIENT_COUNT="num_non_missing(ACHIEVEMENT_LEVEL)",
-                PERCENT_AT_ABOVE_PROFICIENT_PRIOR="percent_in_category(ACHIEVEMENT_LEVEL_PRIOR, list(c('Proficient', 'Advanced')), list(c('Unsatisfactory', 'Partially Proficient', 'Proficient', 'Advanced')))",
-                PERCENT_AT_ABOVE_PROFICIENT_PRIOR_COUNT="num_non_missing(ACHIEVEMENT_LEVEL_PRIOR)"),
-	summary.groups=list(institution=c("STATE", "DISTRICT_NUMBER", "SCHOOL_NUMBER"),
-		content="CONTENT_AREA",
-		time="YEAR",
-		institution_level="GRADE",
-		demographic=c("GENDER", "ETHNICITY", "FREE_REDUCED_LUNCH_STATUS", "ELL_STATUS", "IEP_STATUS", "GIFTED_AND_TALENTED_PROGRAM_STATUS", "CATCH_UP_KEEP_UP_STATUS_INITIAL"),
-		institution_inclusion=list(STATE="STATE_ENROLLMENT_STATUS", DISTRICT_NUMBER="DISTRICT_ENROLLMENT_STATUS", SCHOOL_NUMBER="SCHOOL_ENROLLMENT_STATUS")),
-        confidence.interval.groups=list(TYPE="Bootstrap",
-                VARIABLES=c("SGP"),
-                QUANTILES=c(0.025, 0.975),
-                GROUPS=list(institution="SCHOOL_NUMBER",
-                content="CONTENT_AREA",
-                time="YEAR",
-                institution_level= NULL,
-                demographic=NULL,
-                institution_inclusion=list(STATE=NULL, DISTRICT_NUMBER=NULL, SCHOOL_NUMBER="SCHOOL_ENROLLMENT_STATUS"))),
+	sgPlot.demo.report=FALSE,
+	sgp.summaries=NULL,
+	summary.groups=NULL,
+	confidence.interval.groups=NULL,
 	plot.types=c("bubblePlot", "studentGrowthPlot", "growthAchievementPlot")) {
 
         started.at <- proc.time()
@@ -49,21 +30,23 @@ function(sgp_object,
 		tmp.name <- gsub("_", " ", deparse(substitute(sgp_object)))
 		if (any(sapply(c(state.name, "Demonstration", "sgpData LONG"), function(x) regexpr(x, tmp.name)))==1) {
 			state <- c(state.abb, rep("DEMO", 2))[which(sapply(c(state.name, "Demonstration", "sgpData LONG"), function(x) regexpr(x, tmp.name))==1)]
+		} else {
+			message("\tNOTE: Use of the higher level 'abcSGP' function requires extensive metadata embedded in the 'SGPstateData' list object. Please add your state's data to 'SGPstateData' by examining a state that is currently embedded. For example, SGPstateData[['DEMO']]. Please contact the package administrator with further questions.")
 		}
 	}
 
         ### Check for consistency between simulate.sgps and existence of CSEMs ###
 
 	if (simulate.sgps & is.null(SGPstateData[[state]][["Assessment_Program_Information"]][["CSEM"]])) {
-                message("CSEMs are required in SGPstateData to simulate SGPs for confidence interval calculations. Confidence intervals will not be calculated.")
+                message("\tCSEMs are required in SGPstateData to simulate SGPs for confidence interval calculations. Confidence intervals will not be calculated.")
                 simulate.sgps <- FALSE
         }
 
 
 	### prepareSGP ###
 
 	if ("prepareSGP" %in% steps) {
-		sgp_object <- prepareSGP(sgp_object, var.names=prepareSGP.var.names)
+		sgp_object <- prepareSGP(sgp_object, state=state, var.names=prepareSGP.var.names)
 	        if (save.intermediate.results) save(sgp_object, file="sgp_object.Rdata")
 	}
 
@@ -82,6 +65,14 @@ function(sgp_object,
 	### analyzeSGP ###
 
 	if ("analyzeSGP" %in% steps) {
+
+        ### Check for consistency between simulate.sgps and existence of CSEMs ###
+
+		if (simulate.sgps & is.null(SGPstateData[[state]][["Assessment_Program_Information"]][["CSEM"]])) {
+        	        message("\tCSEMs are required in SGPstateData to simulate SGPs for confidence interval calculations. Confidence intervals will not be calculated.")
+			simulate.sgps <- FALSE
+		}
+
 		sgp_object <- analyzeSGP(
 			sgp_object=sgp_object,
 			state=state,
@@ -127,7 +118,8 @@ function(sgp_object,
 			content_areas=content_areas, 
 			sgp.summaries=sgp.summaries, 
 			summary.groups=summary.groups, 
-			confidence.interval.groups=confidence.interval.groups)
+			confidence.interval.groups=confidence.interval.groups,
+			parallel.config=parallel.config)
 
                 if (save.intermediate.results) save(sgp_object, file="sgp_object.Rdata")
 	}
@@ -143,10 +135,11 @@ function(sgp_object,
 			state=state,
 			bPlot.years=years,
 			sgPlot.years=years,
-			sgPlot.demo.report=TRUE,
+			sgPlot.demo.report=sgPlot.demo.report,
 			gaPlot.years=years,
 			bPlot.content_areas=content_areas,
-			gaPlot.content_areas=content_areas)
+			gaPlot.content_areas=content_areas,
+			parallel.config=parallel.config)
 	}
 
         message(paste("Finished abcSGP", date(), "in", timetaken(started.at), "\n"))