Asymptotic Standard Error Sas
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row and column variables of the contingency table. The following are measures of ordinal association that consider whether the column variable Y tends to increase as the row variable X increases: gamma, Kendall’s tau-, Stuart’s tau-, standard error sas proc means and Somers’ . These measures are appropriate for ordinal variables, and they classify pairs
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of observations as concordant or discordant. A pair is concordant if the observation with the larger value of X also has the robust standard error sas larger value of Y. A pair is discordant if the observation with the larger value of X has the smaller value of Y. See Agresti (2007) and the other references cited for the individual measures
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of association. The Pearson correlation coefficient and the Spearman rank correlation coefficient are also appropriate for ordinal variables. The Pearson correlation describes the strength of the linear association between the row and column variables, and it is computed by using the row and column scores specified by the SCORES= option in the TABLES statement. The Spearman correlation is computed with rank scores. The polychoric correlation (requested by the PLCORR option) also requires confidence interval sas ordinal variables and assumes that the variables have an underlying bivariate normal distribution. The following measures of association do not require ordinal variables and are appropriate for nominal variables: lambda asymmetric, lambda symmetric, and the uncertainty coefficients. PROC FREQ computes estimates of the measures according to the formulas given in the following sections. For each measure, PROC FREQ computes an asymptotic standard error (), which is the square root of the asymptotic variance denoted by in the following sections. Confidence Limits If you specify the CL option in the TABLES statement, PROC FREQ computes asymptotic confidence limits for all MEASURES statistics. The confidence coefficient is determined according to the value of the ALPHA= option, which, by default, equals 0.05 and produces 95% confidence limits. The confidence limits are computed as where is the estimate of the measure, is the th percentile of the standard normal distribution, and is the asymptotic standard error of the estimate. Asymptotic Tests For each measure that you specify in the TEST statement, PROC FREQ computes an asymptotic test of the null hypothesis that the measure equals zero. Asymptotic tests are available for the following measures of association: gamma, Kendall’s tau-, Stuart’s tau-, Somers’ , Somers’ , the Pearson correlation coefficient, and the Spearman rank correlation coeffi
StatementWEIGHT Statement Details Inputting Frequency CountsGrouping with FormatsMissing ValuesIn-Database ComputationStatistical ComputationsComputational ResourcesOutput Data SetsDisplayed OutputODS Table NamesODS Graphics Examples Output Data Set
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of FrequenciesFrequency Dot PlotsChi-Square Goodness-of-Fit TestsBinomial ProportionsAnalysis of a 2x2
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Contingency TableOutput Data Set of Chi-Square StatisticsCochran-Mantel-Haenszel StatisticsCochran-Armitage Trend TestFriedman’s Chi-Square TestCochran’s Q Test References coefficient of variation sas EXACT Statement Statistic Options Computation Options EXACT statistic-options computation-options> ; The EXACT statement requests exact tests and confidence limits for selected statistics. The http://support.sas.com/documentation/cdl/en/procstat/63104/HTML/default/procstat_freq_a0000000659.htm statistic-options identify which statistics to compute, and the computation-options specify options for computing exact statistics. See the section Exact Statistics for details. Note: PROC FREQ computes exact tests by using fast and efficient algorithms that are superior to direct enumeration. Exact tests are appropriate when a data set is small, http://support.sas.com/documentation/cdl/en/statug/65328/HTML/default/statug_freq_syntax03.htm sparse, skewed, or heavily tied. For some large problems, computation of exact tests might require a considerable amount of time and memory. Consider using asymptotic tests for such problems. Alternatively, when asymptotic methods might not be sufficient for such large problems, consider using Monte Carlo estimation of exact p-values. You can request Monte Carlo estimation by specifying the MC computation-option in the EXACT statement. See the section Computational Resources for more information. Statistic Options The statistic-options specify which exact tests and confidence limits to compute. Table 38.6 lists the available statistic-options and the exact statistics that are computed. Descriptions of the statistic-options follow the table in alphabetical order. For one-way tables, exact p-values are available for binomial proportion tests, the chi-square goodness-of-fit test, and the likelihood ratio chi-square test. Exact (Clopper-Pearson) confidence limits are available for the binomial proportion. For two-way tables, exact p-values are available for
This table provides the number of levels for all variables named in the TABLES statements. PROC FREQ determines the variable levels from the formatted variable values. See Grouping with Formats http://support.sas.com/documentation/cdl/en/procstat/63104/HTML/default/procstat_freq_sect021.htm for details. The "Number of Variable Levels" table contains the following information: Variable name Levels, which is the total number of levels of the variable Number of Nonmissing Levels, if there are missing levels for any of the variables Number of Missing Levels, if there are missing levels for any of the variables One-Way Frequency Tables PROC FREQ displays one-way frequency tables for all one-way table requests in the TABLES standard error statements, unless you specify the NOPRINT option in the PROC statement or the NOPRINT option in the TABLES statement. For a one-way table showing the frequency distribution of a single variable, PROC FREQ displays the name of the variable and its values. For each variable value or level, PROC FREQ displays the following information: Frequency count, which is the number of observations in the level Test Frequency count, if standard error sas you specify the CHISQ and TESTF= options to request a chi-square goodness-of-fit test for specified frequencies Percent, which is the percentage of the total number of observations. (The NOPERCENT option suppresses this information.) Test Percent, if you specify the CHISQ and TESTP= options to request a chi-square goodness-of-fit test for specified percents. (The NOPERCENT option suppresses this information.) Cumulative Frequency count, which is the sum of the frequency counts for that level and all other levels listed above it in the table. The last cumulative frequency is the total number of nonmissing observations. (The NOCUM option suppresses this information.) Cumulative Percent, which is the percentage of the total number of observations in that level and in all other levels listed above it in the table. (The NOCUM or the NOPERCENT option suppresses this information.) The one-way table also displays the Frequency Missing, which is the number of observations with missing values. Statistics for One-Way Frequency Tables For one-way tables, two statistical options are available in the TABLES statement. The CHISQ option provides a chi-square goodness-of-fit test, and the BINOMIAL option provides binomial proportion statistics and tests. PROC FREQ displays the following information, unless you specify the NOPRINT option in the PROC statement: If you specify the
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