{"component": "clause", "props": {"groups": [{"snippet_links": [{"key": "agrees-to", "type": "clause", "offset": [4, 13]}, {"key": "student-data", "type": "clause", "offset": [24, 36]}, {"key": "data-warehouse", "type": "clause", "offset": [55, 69]}, {"key": "analytical-reports", "type": "definition", "offset": [83, 101]}, {"key": "distributions-of", "type": "clause", "offset": [119, 135]}, {"key": "the-district", "type": "clause", "offset": [175, 187]}, {"key": "dhs-shall", "type": "clause", "offset": [254, 263]}, {"key": "successes-and-challenges", "type": "clause", "offset": [327, 351]}, {"key": "critical-reflection", "type": "definition", "offset": [353, 372]}, {"key": "all-parties", "type": "definition", "offset": [408, 419]}, {"key": "the-data", "type": "clause", "offset": [466, 474]}, {"key": "to-develop", "type": "definition", "offset": [488, 498]}, {"key": "working-with-children", "type": "definition", "offset": [562, 583]}, {"key": "in-the-community", "type": "definition", "offset": [810, 826]}], "size": 3, "snippet": "DHS agrees to integrate student data into its existing data warehouse and generate analytical reports that provide the distributions of students receiving DHS services across the District. The analytical reports shall be de-identified aggregate reports. DHS shall identify attributes and indicators for academic and behavioral successes and challenges. Critical Reflection. DHS shall present the analysis to all parties and together engage in careful examination of the data in an effort to develop effective strategies for improving both organizations\u2019 ways of working with children and families. Action. DHS shall create, implement, and assess strategies developed through the statistical analysis and critical reflection phases. DHS shall work with the District to implement these strategies in schools and in the community.", "samples": [{"hash": "aqVgtdz64Sj", "uri": "/contracts/aqVgtdz64Sj#statistical-analysis", "label": "Memorandum of Understanding", "score": 23.4536972046, "published": true}, {"hash": "hMNSNnAt77x", "uri": "/contracts/hMNSNnAt77x#statistical-analysis", "label": "Memorandum of Understanding", "score": 21.4120464325, "published": true}], "hash": "798600dc8ed3ef519b1515e8cab28894", "id": 4}, {"snippet_links": [{"key": "quality-acceptance", "type": "definition", "offset": [54, 72]}, {"key": "the-f", "type": "clause", "offset": [79, 84]}, {"key": "to-determine", "type": "clause", "offset": [122, 134]}, {"key": "the-t", "type": "clause", "offset": [203, 208]}, {"key": "in-addition-to", "type": "clause", "offset": [316, 330]}, {"key": "types-of", "type": "clause", "offset": [341, 349]}, {"key": "independent-verification", "type": "clause", "offset": [360, 384]}, {"key": "to-validate", "type": "definition", "offset": [435, 446]}, {"key": "acceptance-test-results", "type": "clause", "offset": [459, 482]}], "size": 5, "snippet": "31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.", "samples": [{"hash": "lg6qBrwd4tv", "uri": "/contracts/lg6qBrwd4tv#statistical-analysis", "label": "Design Build Maintain Agreement", "score": 24.7019367218, "published": true}, {"hash": "aaiYXGH91QU", "uri": "/contracts/aaiYXGH91QU#statistical-analysis", "label": "Design Build Maintain Agreement", "score": 24.7019367218, "published": true}, {"hash": "j3z2zLMNUbr", "uri": "/contracts/j3z2zLMNUbr#statistical-analysis", "label": "Design Build Maintain Agreement", "score": 24.6636142731, "published": true}], "hash": "13acc22c7454bda6aef229eed30902b4", "id": 1}, {"snippet_links": [{"key": "behavioral-objectives", "type": "definition", "offset": [0, 21]}, {"key": "in-order-to", "type": "clause", "offset": [23, 34]}, {"key": "the-student", "type": "clause", "offset": [59, 70]}, {"key": "statistical-methods", "type": "definition", "offset": [124, 143]}, {"key": "not-required", "type": "definition", "offset": [247, 259]}, {"key": "this-agreement", "type": "clause", "offset": [271, 285]}], "size": 4, "snippet": "Behavioral Objectives: In order to attain this competency, the student should be able to: Perform a laboratory that applies statistical methods to the analysis of experimental data, real or simulated (This competency is recommended by the ACS but not required as part of this agreement).", "samples": [{"hash": "f3uh0fH9pIC", "uri": "/contracts/f3uh0fH9pIC#statistical-analysis", "label": "Program to Program Articulation Agreement", "score": 23.3760356903, "published": true}, {"hash": "jj22SvI0nCq", "uri": "/contracts/jj22SvI0nCq#statistical-analysis", "label": "Program to Program Articulation Agreement", "score": 22.6287345886, "published": true}, {"hash": "eKlAeB6q9lB", "uri": "/contracts/eKlAeB6q9lB#statistical-analysis", "label": "Articulation Agreement", "score": 22.3760356903, "published": true}], "hash": "5af42f2a16e8e6e82a3ddf5957f06183", "id": 2}, {"snippet_links": [{"key": "statistical-analyses", "type": "clause", "offset": [11, 31]}, {"key": "college-station", "type": "clause", "offset": [113, 128]}, {"key": "the-percentage", "type": "definition", "offset": [140, 154]}, {"key": "correlation-analysis", "type": "clause", "offset": [231, 251]}, {"key": "relationship-between", "type": "clause", "offset": [280, 300]}, {"key": "category-3", "type": "definition", "offset": [518, 528]}, {"key": "to-determine", "type": "clause", "offset": [547, 559]}, {"key": "ratio-of", "type": "clause", "offset": [638, 646]}, {"key": "total-number-of", "type": "definition", "offset": [736, 751]}], "size": 3, "snippet": "All of the statistical analyses were performed with dedicated software (Stata Statistical version 12; StataCorp, College Station, TX, USA). The percentage of sectors with residual cancer was calculated for each score, and \u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587 correlation analysis was performed to assess the relationship between percentage and PI-RR score. The per-sector sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with the detection of the sector with residual cancer were calculated at PI-RR category 3 and 4 thresholds. To determine sensitivity, the cancer detection rate (CDR) per sector was calculated as the ratio of the number of sectors with suspicious MRI findings ultimately confirmed to be PCa to the total number of sectors with residual lesions found on histology; this was B C D E T2WI DWI ADC DCE PI-RR category", "samples": [{"hash": "c6wJiG2JxZu", "uri": "/contracts/c6wJiG2JxZu#statistical-analysis", "label": "Research Article", "score": 33.2698974609, "published": true}, {"hash": "kdfwXN2qQ8", "uri": "/contracts/kdfwXN2qQ8#statistical-analysis", "label": "Diagnostic Efficacy and Interobserver Agreement Study", "score": 33.2616844177, "published": true}, {"hash": "bn9SNj1JNiy", "uri": "/contracts/bn9SNj1JNiy#statistical-analysis", "label": "Diagnostic Efficacy and Interobserver Agreement Study", "score": 33.2479972839, "published": true}], "hash": "d0b43fcd84ccf18e3d73dcab545a794a", "id": 3}, {"snippet_links": [{"key": "statistical-methods", "type": "definition", "offset": [9, 28]}, {"key": "calculate-the", "type": "clause", "offset": [42, 55]}, {"key": "the-distributions", "type": "clause", "offset": [216, 233]}, {"key": "according-to", "type": "definition", "offset": [308, 320]}, {"key": "a-\u2587", "type": "clause", "offset": [334, 337]}, {"key": "randomly-selected", "type": "definition", "offset": [669, 686]}, {"key": "a-p", "type": "clause", "offset": [971, 974]}, {"key": "gold-standard", "type": "definition", "offset": [992, 1005]}, {"key": "step-in", "type": "definition", "offset": [1147, 1154]}, {"key": "the-execution", "type": "clause", "offset": [1169, 1182]}, {"key": "standard-method", "type": "definition", "offset": [1460, 1475]}, {"key": "other-method", "type": "clause", "offset": [1529, 1541]}, {"key": "to-zero", "type": "definition", "offset": [1612, 1619]}, {"key": "the-panel", "type": "clause", "offset": [1897, 1906]}, {"key": "limits-of-agreement", "type": "clause", "offset": [2161, 2180]}, {"key": "the-data", "type": "clause", "offset": [2509, 2517]}, {"key": "the-\u2587", "type": "clause", "offset": [2641, 2646]}, {"key": "in-order-to", "type": "clause", "offset": [2664, 2675]}, {"key": "the-selected", "type": "clause", "offset": [2995, 3007]}, {"key": "competitions-and-events", "type": "clause", "offset": [3042, 3065]}, {"key": "interpretation-of-agreement", "type": "clause", "offset": [3184, 3211]}, {"key": "software-version", "type": "definition", "offset": [3986, 4002]}, {"key": "ibm-corp", "type": "clause", "offset": [4009, 4017]}], "size": 3, "snippet": "Standard statistical methods were used to calculate the means, standard deviations, and absolute and relative frequencies. The Kolmogorov-Smirnov and \u2587\u2587\u2587\u2587\u2587\u2587 tests were used to assess the normality and homogeneity of the distributions respectively; data were analysed using parametric or non-parametric tests according to the results. A \u2587\u2587\u2587\u2587- \u2587\u2587\u2587\u2587\u2587\u2587\u2587 test or unpaired t-test was used to evaluate the differences between the Control and Panel Qualification and Final scores respectively. The reliability between E/A C&P-scores was calculated using a one way-random, absolute agreement Intraclass Coefficient of Correlation (ICC), because each routine was rated by judges randomly selected from a larger population of judges. ICC values less than 0.5, between 0.5 and 0.75, between 0.75 and 0.9, and greater than 0.90 are indicative of poor, moderate, good, and excellent reliability respectively (\u2587\u2587\u2587 & \u2587\u2587, 2016). Validity was assessed by comparing the concrete judging (E/A P-scores) with the gold standard score (E/A C-Score). Systematic over- or under-rating of scoring, also known as bias (\u2587\u2587\u2587\u2587\u2587 et al., 2012) was also investigated as a further step in the analysis. The Execution/Artistic differences were computed as the differences between the two human scoring systems, which indicated bias, i.e. systematic under- or over-estimation of Execution/Artistic scores. These differences were defined as: E/A C-P bias = E/A C-Score \u2013 E/A P-scores. If the gold standard method (E/A C-Score) is sometimes higher, and sometimes the other method (E/A P-Score) is higher, the average of the differences will be close to zero. If it is not close to zero, this indicates that the two assay methods are systematically producing different results. Assuming that the E/A C-Scores, given by the highest category of judges, are accurate, the concordance value would show to what extent the scores assigned by the panel are correct. \u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587\u2587 plots (\u2587\u2587\u2587\u2587\u2587 & \u2587\u2587\u2587\u2587\u2587\u2587, 1986) were used to assess and display agreement along the entire spectrum of scores and at each Qualitative Performance Range in Qualification and Final competition. Systematic C-P scores bias and the 95% limits of agreement (LoA = C-P scores bias \u00b11.96 SD) were calculated. Each \u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587\u2587 plot shows the limits of agreement (LoA), calculated by using the mean \u00b12 standard deviations of the differences between the two E/A C-P scores. The difference of the two paired measurements is plotted against the mean of the same two measurements, and 95% of the data points should lie within \u00b12 standard deviations of the mean differences. The maximum FIG allowed deviation was included in the \u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587\u2587 plot, in order to assess the findings for clinical significance for each Qualitative Performance Range. Non-parametric methods such as \u2587\u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587 survival-agreement plots (\u2587\u2587\u2587\u2587 et al., 2003) and the Log Rank Test were used to evaluate the probability of a certain magnitude occurring in the differences between C-P scores bias data in the selected Qualitative Performance Ranges in competitions and events. The \u2587\u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587 plots provided a graphical approach as a complement to the \u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587\u2587 method and allowed a simple interpretation of agreement, taking into account the \u201cclinical\u201d importance of the inter-score differences. \u2587\u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587 plots allow analysis of reliability or agreement by means of survival analysis techniques (\u2587\u2587\u2587\u2587 et al., 2003). On the \u2587\u2587\u2587\u2587\u2587\u2587-\u2587\u2587\u2587\u2587\u2587 plot, the horizontal axis shows the absolute difference between two E/A C-P Score measurements for each routine and the vertical axis shows the proportion of cases in which the discrepancies equal at least each of the observed differences. The graph is thus constructed the same way as for a survival analysis, where the 0-difference values are removed, and the variable \u201ctime\u201d is replaced by the absolute differences between the E/ A C-P Scores measurements. Significance was accepted at the P \u2264 0.05 level and all analyses were performed using SPSS software version 26.0 (IBM Corp., Armonk, NY, USA).", "samples": [{"hash": "lhD5qVs1Ut7", "uri": "/contracts/lhD5qVs1Ut7#statistical-analysis", "label": "Peer Reviewed Version", "score": 24.045173645, "published": true}, {"hash": "86trQIUaXyi", "uri": "/contracts/86trQIUaXyi#statistical-analysis", "label": "Publication", "score": 24.045173645, "published": true}], "hash": "d59277cbf057eafb44d3ac67ca3cd917", "id": 5}, {"snippet_links": [{"key": "dependent-variable", "type": "clause", "offset": [86, 104]}, {"key": "close-to", "type": "definition", "offset": [239, 247]}, {"key": "generalized-linear", "type": "definition", "offset": [438, 456]}, {"key": "other-variables", "type": "clause", "offset": [785, 800]}, {"key": "sensitivity-analyses", "type": "clause", "offset": [842, 862]}, {"key": "based-on", "type": "definition", "offset": [934, 942]}, {"key": "a-\u2587", "type": "clause", "offset": [992, 995]}, {"key": "into-effect", "type": "clause", "offset": [1187, 1198]}, {"key": "transitional-period", "type": "clause", "offset": [1212, 1231]}, {"key": "the-g", "type": "clause", "offset": [1301, 1306]}, {"key": "if-required", "type": "definition", "offset": [1315, 1326]}, {"key": "an-additional", "type": "clause", "offset": [1341, 1354]}, {"key": "the-arbitration-board", "type": "clause", "offset": [1476, 1497]}], "size": 2, "snippet": "After analyzing price premiums descriptively, we estimated six regression models. The dependent variable (i.e., the relation between a pharmaceutical\u2019s costs and those of its comparator) appeared to be gamma-distributed (many values at or close to 0), which we con\ufb01rmed by applying the Modi\ufb01ed Park Test [43]. Therefore, we could not use a simple ordinary least squares (OLS) regression. To avoid retransformation problems we preferred a generalized linear model (GLM) over a log OLS model [43]. Applying the Pregibon Goodness of Link Test [44] we con\ufb01rmed the usage of a log-link. Thus, we used a GLM with a log-link function to analyze the impact of added bene\ufb01t on price pre- miums. To allow for meaningful interpretation, we calculated marginal effects for each variable, with all other variables set to their means. We conducted several sensitivity analyses. First, because single observations may have a large impact on results based on such a small sample, we excluded substances with a \u2587\u2587\u2587\u2587\u2019\u2587 D greater than the conventional cutoff point of 4/n [45]. Second, we controlled for whether pharmaceuticals had been assessed dur- ing the \ufb01rst 7 months after the AMNOG legislation came into effect. During this transitional period, manufacturers were advised on the completeness of their dossiers by the G-BA and, if required, were granted an additional 3 months to complete them [46]. Third, we included a variable that controlled for whether the \ufb01nal price had been set by the arbitration board. Last, instead of using average comparator costs when several interchangeable comparators were eligible for the same patient subgroup, we reran our models using the least and the most costly comparators. All analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC).", "samples": [{"hash": "jBaZpxKzqPE", "uri": "/contracts/jBaZpxKzqPE#statistical-analysis", "label": "Price Negotiation Agreement", "score": 19.7645454407, "published": true}, {"hash": "gnqsnOpGRFo", "uri": "/contracts/gnqsnOpGRFo#statistical-analysis", "label": "Price Negotiation Agreement", "score": 19.7645454407, "published": true}], "hash": "3b753efe9b962753977c356e5395527e", "id": 6}, {"snippet_links": [], "size": 2, "snippet": "SPSS (v17.0) was used for all statistical analysis. All data are presented as mean", "samples": [{"hash": "hIaNXNO2Te", "uri": "/contracts/hIaNXNO2Te#statistical-analysis", "label": "End User License Agreement", "score": 21.2505130768, "published": true}, {"hash": "h5ODrjsoJ0J", "uri": "/contracts/h5ODrjsoJ0J#statistical-analysis", "label": "End User License Agreement", "score": 21.2505130768, "published": true}], "hash": "4c6e0abeda5a037dbe65ff7fbcb22e55", "id": 7}, {"snippet_links": [{"key": "core-team", "type": "definition", "offset": [317, 326]}], "size": 2, "snippet": "We conducted a series of analyses to obtain the following estimates: (1) associations between SES indicators and depression symptoms; (2) estimates from univariate twin analyses; (3) estimates from biometric bivariate moderation (GxE) analyses. All analyses were conducted in R v.4.0.2 (https://www.R-project.org/; R Core Team, 2020).", "samples": [{"hash": "655iYnI8JnT", "uri": "/contracts/655iYnI8JnT#statistical-analysis", "label": "End User License Agreement", "score": 31.8509254456, "published": true}, {"hash": "2QgAYpMcCr6", "uri": "/contracts/2QgAYpMcCr6#statistical-analysis", "label": "End User License Agreement", "score": 25.0951404572, "published": true}], "hash": "f45dc9e61704d704c8d66c795f8e5f23", "id": 8}, {"snippet_links": [{"key": "agreement-between", "type": "clause", "offset": [8, 25]}, {"key": "total-agreement", "type": "definition", "offset": [69, 84]}, {"key": "the-\u2587", "type": "clause", "offset": [149, 154]}, {"key": "of-agreement", "type": "clause", "offset": [207, 219]}, {"key": "account-for-the", "type": "clause", "offset": [270, 285]}, {"key": "reduction-of", "type": "clause", "offset": [519, 531]}, {"key": "very-good", "type": "clause", "offset": [850, 859]}, {"key": "statistically-significant-differences", "type": "clause", "offset": [965, 1002]}, {"key": "distribution-of", "type": "clause", "offset": [1010, 1025]}, {"key": "the-percentage", "type": "definition", "offset": [1134, 1148]}, {"key": "positive-results", "type": "definition", "offset": [1152, 1168]}, {"key": "the-risk", "type": "definition", "offset": [1194, 1202]}, {"key": "a-\u2587", "type": "clause", "offset": [1298, 1301]}], "size": 2, "snippet": "For the agreement between the 2 cytology raters, we calcu- lated the total agreement with a binomial 95% confidence interval (95% CI). We calculated the \u2587\u2587\u2587\u2587\u2587 kappa with 95% CI as a chance-corrected measure of agreement as described by \u2587\u2587\u2587\u2587\u2587\u2587\u2587.18 Because kappa does not account for the degree of disagreement between categories and treats any disagreement equally, we calculated linear- weighted kappa with 95% CI for the ordered cytology cat- egories. Thus, disagreement between adjacent categories results in a lower reduction of kappa values than disagree- ment between nonadjacent categories. Kappa values < 0.20 were interpreted as poor, values between 0.21 and 0.40 were interpreted as fair, values between 0.41 and 0.60 were interpreted as moderate, values between 0.61 and 0.80 were interpreted as good, and values > 0.80 were interpreted as very good. Exact versions of symmetry (4-category) and \u2587\u2587\u2587\u2587\u2587\u2587\u2587 (2-category) chi-square tests were used to test for statistically significant differences in the distribution of the cytologic interpretations between raters. A nonparametric test of trend was used to assess the trend in the percentage of positive results for each bio- marker for the risk of AIN2 or higher (AIN2+) with increasing severity of the cytologic interpretation.19 Finally, a \u2587\u2587\u2587\u2587\u2587\u2587 exact test was used to test for differences in the percentage of positive results for each biomarker between subgroups defined by the paired cytologic interpretations.", "samples": [{"hash": "cKmchgIRCRp", "uri": "/contracts/cKmchgIRCRp#statistical-analysis", "label": "Interrater Agreement of Anal Cytology", "score": 21.4280452728, "published": true}, {"hash": "5XunIUYQmJ4", "uri": "/contracts/5XunIUYQmJ4#statistical-analysis", "label": "Interrater Agreement of Anal Cytology", "score": 19.379611969, "published": true}], "hash": "c0ca7e8c3367ba880f8fdd87bc4371bb", "id": 9}, {"snippet_links": [{"key": "to-determine", "type": "clause", "offset": [0, 12]}, {"key": "correlation-coefficient", "type": "definition", "offset": [69, 92]}], "size": 2, "snippet": "To determine interobserver agreement, we calculated the intra- class correlation coefficient with the 2-way random-effects model by using SPSS v.", "samples": [{"hash": "hbaHrtDow6I", "uri": "/contracts/hbaHrtDow6I#statistical-analysis", "label": "Interobserver Agreement Study", "score": 20.7015743256, "published": true}, {"hash": "9f4k2behxnA", "uri": "/contracts/9f4k2behxnA#statistical-analysis", "label": "Interobserver Agreement Study", "score": 20.7015743256, "published": true}], "hash": "8f1a31ddcb762b1d0e3e10f9bffb26fd", "id": 10}], "next_curs": "Cl0SV2oVc35sYXdpbnNpZGVyY29udHJhY3RzcjkLEhZDbGF1c2VTbmlwcGV0R3JvdXBfdjU2Ih1zdGF0aXN0aWNhbC1hbmFseXNpcyMwMDAwMDAwYQyiAQJlbhgAIAA=", "clause": {"parents": [["methods", "Methods"], ["materials-and-methods", "Materials and Methods"], ["method", "Method"], ["material-and-methods", "Material and Methods"], ["trial-activities-and-responsibilities", "Trial Activities and Responsibilities"]], "size": 171, "children": [["", ""], ["safety-analyses", "Safety Analyses"], ["introduction", "Introduction"], ["limitations", "Limitations"], ["discussion", "Discussion"]], "title": "Statistical Analysis", "id": "statistical-analysis", "related": [["statistical-data", "Statistical Data", "Statistical Data"], ["statistical-sampling-documentation", "Statistical Sampling Documentation", "Statistical Sampling Documentation"], ["statistical-demographic-or-market-related-data", "Statistical, Demographic or Market-Related Data", "Statistical, Demographic or Market-Related Data"], ["statistical-and-market-data", "Statistical and Market Data", "Statistical and Market Data"], ["statistical-and-marketing-related-data", "Statistical and Marketing-Related Data", "Statistical and Marketing-Related Data"]], "related_snippets": [], "updated": "2025-07-24T04:27:51+00:00"}, "json": true, "cursor": ""}}