pisaedTable1REF <- c( "", "Formula: math ~ st04q01 + st20q01 ", "", "Plausible values: 5", "jrrIMax: 1", "Weight variable: 'w_fstuwt'", "Variance method: jackknife", "JK replicates: 80", "full data n: 4978", "n used: 4873", "", "", "Summary Table:", " st04q01 st20q01 N WTD_N PCT SE(PCT) MEAN SE(MEAN)", " Female Country of test 2234 1575416.5 92.425753 0.8038984 481.1794 4.019205", " Female Other country 180 129104.6 7.574247 0.8038984 463.6272 10.355889", " Male Country of test 2272 1611412.6 91.796017 0.9558501 486.8819 3.853613", " Male Other country 187 144015.0 8.203983 0.9558501 474.1468 9.474347" ) plm1REF <- c( " (Intercept) st29q06Agree st29q06Disagree st29q06Strongly disagree sc01q01Private ", " 506.993125 -21.828757 -32.381549 -52.944871 2.408131 " ) pgap1REF <- c( "Call: gap(variable = \"math\", data = usaINT2012, groupA = st04q01 == ", " \"Male\", groupB = st04q01 == \"Female\", weightVar = \"w_fstuwt\")", "", "Labels:", " group definition nFullData nUsed", " A st04q01 == \"Male\" 4978 2525", " B st04q01 == \"Female\" 4978 2453", "", "Percentage:", " pctA pctAse pctB pctBse diffAB covAB diffABse diffABpValue dofAB", " 50.98087 0.71829 49.019 0.71829 1.9617 -0.51594 1.4366 0.1749 110.03", "", "Results:", " estimateA estimateAse estimateB estimateBse diffAB covAB diffABse diffABpValue dofAB", " 483.647 3.8003 479 3.9211 4.6517 11.019 2.7891 0.09911 83.141" ) al1REF <- c( "", "AchievementVars: cpro", "aggregateBy: st04q01", "", "Achievement Level Cutpoints:", "358.49 423.42 488.35 553.28 618.21 683.14 ", "", "Plausible values: 5", "jrrIMax: 1", "Weight variable: 'w_fstuwt'", "Variance method: jackknife", "JK replicates: 80", "full data n: 5177", "n used: 5177", "", "", "Discrete", " cpro_Level st04q01 N wtdN Percent StandardError", " Below Proficiency Level 1 Female 95.4 1541.697 3.539350 0.7086689", " At Proficiency Level 1 Female 234.2 3815.988 8.760555 0.8224039", " At Proficiency Level 2 Female 524.6 8669.991 19.904132 0.9013387", " At Proficiency Level 3 Female 771.0 12722.017 29.206570 1.3662494", " At Proficiency Level 4 Female 644.6 10711.838 24.591702 1.3001839", " At Proficiency Level 5 Female 300.8 4985.134 11.444621 1.1955623", " At Proficiency Level 6 Female 66.4 1112.086 2.553071 0.5394964", " Below Proficiency Level 1 Male 68.8 1083.360 2.616423 0.5358135", " At Proficiency Level 1 Male 167.6 2578.450 6.227218 0.6980039", " At Proficiency Level 2 Male 383.8 6222.924 15.028992 1.1775214", " At Proficiency Level 3 Male 648.8 10591.764 25.580183 1.3363213", " At Proficiency Level 4 Male 696.6 11515.983 27.812266 1.7109083", " At Proficiency Level 5 Male 430.6 7036.873 16.994760 1.1910320", " At Proficiency Level 6 Male 143.8 2376.777 5.740157 0.6795269" ) pgap2REF <- c( "gapList", "Call: gap(variable = \"math\", data = usaINT2012, groupA = st04q01 == ", " \"Male\", groupB = st04q01 == \"Female\", percentiles = c(50, ", " 90), weightVar = \"w_fstuwt\", pctMethod = \"symmetric\")", "", "Labels:", " group definition", " A st04q01 == \"Male\"", " B st04q01 == \"Female\"", "", "Percentage:", " pctA pctAse pctB pctBse diffAB covAB diffABse diffABpValue dofAB", " 50.98087 0.71829 49.019 0.71829 1.9617 -0.51594 1.4366 0.1749 110.03", "", "Results:", " percentiles estimateA estimateAse estimateB estimateBse diffAB covAB diffABse diffABpValue dofAB", " 50 480.71 4.0760 474.63 4.4988 6.0858 11.4942 3.7235 0.1064 73.67", " 90 605.17 3.9426 595.39 8.6030 9.7794 7.8932 8.5889 0.2579 89.17" ) pvREF <- c( "There are 10 subject scale(s) or subscale(s) in this edsurvey.data.frame:", "'math' subject scale or subscale with 5 plausible values (the default).", " The plausible value variables are: 'pv1math', 'pv2math', 'pv3math', 'pv4math', and 'pv5math'", "", "'macc' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1macc', 'pv2macc', 'pv3macc', 'pv4macc', and 'pv5macc'", "", "'macq' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1macq', 'pv2macq', 'pv3macq', 'pv4macq', and 'pv5macq'", "", "'macs' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1macs', 'pv2macs', 'pv3macs', 'pv4macs', and 'pv5macs'", "", "'macu' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1macu', 'pv2macu', 'pv3macu', 'pv4macu', and 'pv5macu'", "", "'mape' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1mape', 'pv2mape', 'pv3mape', 'pv4mape', and 'pv5mape'", "", "'mapf' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1mapf', 'pv2mapf', 'pv3mapf', 'pv4mapf', and 'pv5mapf'", "", "'mapi' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1mapi', 'pv2mapi', 'pv3mapi', 'pv4mapi', and 'pv5mapi'", "", "'read' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1read', 'pv2read', 'pv3read', 'pv4read', and 'pv5read'", "", "'scie' subject scale or subscale with 5 plausible values.", " The plausible value variables are: 'pv1scie', 'pv2scie', 'pv3scie', 'pv4scie', and 'pv5scie'", "" ) swREF <- c( "There is 1 full sample weight in this edsurvey.data.frame:", " 'w_fstuwt' with 80 JK replicate weights (the default).", " Jackknife replicate weight variables associated with the full sample weight 'w_fstuwt':", " 'w_fstr1', 'w_fstr2', 'w_fstr3', 'w_fstr4', 'w_fstr5', 'w_fstr6', 'w_fstr7', 'w_fstr8', 'w_fstr9', 'w_fstr10', 'w_fstr11', 'w_fstr12', 'w_fstr13', 'w_fstr14', 'w_fstr15', 'w_fstr16', 'w_fstr17', 'w_fstr18', 'w_fstr19', 'w_fstr20', 'w_fstr21', 'w_fstr22', 'w_fstr23', 'w_fstr24', 'w_fstr25', 'w_fstr26', 'w_fstr27', 'w_fstr28', 'w_fstr29', 'w_fstr30', 'w_fstr31', 'w_fstr32', 'w_fstr33', 'w_fstr34', 'w_fstr35', 'w_fstr36', 'w_fstr37',", " 'w_fstr38', 'w_fstr39', 'w_fstr40', 'w_fstr41', 'w_fstr42', 'w_fstr43', 'w_fstr44', 'w_fstr45', 'w_fstr46', 'w_fstr47', 'w_fstr48', 'w_fstr49', 'w_fstr50', 'w_fstr51', 'w_fstr52', 'w_fstr53', 'w_fstr54', 'w_fstr55', 'w_fstr56', 'w_fstr57', 'w_fstr58', 'w_fstr59', 'w_fstr60', 'w_fstr61', 'w_fstr62', 'w_fstr63', 'w_fstr64', 'w_fstr65', 'w_fstr66', 'w_fstr67', 'w_fstr68', 'w_fstr69', 'w_fstr70', 'w_fstr71', 'w_fstr72', 'w_fstr73', 'w_fstr74',", " 'w_fstr75', 'w_fstr76', 'w_fstr77', 'w_fstr78', 'w_fstr79', and 'w_fstr80'", "" ) scREF <- c( "Achievement Levels:", " Mathematics: 357.77, 420.07, 482.38, 544.68, 606.99, 669.3", " Problem Solving: 358.49, 423.42, 488.35, 553.28, 618.21, 683.14", " Reading: 262.04, 334.75, 407.47, 480.18, 552.89, 625.61, 698.32" )