The 1xc table CIs

the_1xc_table_CIs(n, alpha = 0.05)

Arguments

n

the observed counts (a 1xc vector, where c is the number of categories)

alpha

the nominal level, e.g. 0.05 for 95# CIs

Value

NULL. This function should be called for its printed output

Examples

# Genotype counts for SNP rs 6498169 in RA patients
the_1xc_table_CIs(n = snp6498169$complete$n)
#> Interval method                 Simultaneous CIs     width 
#> ---------------------------------------------------------- 
#> Estimate of pi_1: 0.3566 
#> Gold Wald                       0.3144 to 0.3987    0.0843 
#> Goodman Wald                    0.3154 to 0.3978    0.0824 
#> Quesenberry-Hurst Wilson score  0.3157 to 0.3997    0.0840 
#> Goodman Wilson score            0.3166 to 0.3987    0.0822 
#> Estimate of pi_2: 0.4910 
#> Gold Wald                       0.4470 to 0.5349    0.0880 
#> Goodman Wald                    0.4479 to 0.5340    0.0860 
#> Quesenberry-Hurst Wilson score  0.4472 to 0.5348    0.0876 
#> Goodman Wilson score            0.4482 to 0.5339    0.0857 
#> Estimate of pi_3: 0.1525 
#> Gold Wald                       0.1208 to 0.1841    0.0633 
#> Goodman Wald                    0.1215 to 0.1834    0.0619 
#> Quesenberry-Hurst Wilson score  0.1235 to 0.1867    0.0632 
#> Goodman Wilson score            0.1241 to 0.1859    0.0618 
#> ---------------------------------------------------------- 
#> The Goodman Wald simultaneous intervals for differences (Bonferroni)
#>   pi_1 - pi_2: estimate = -0.1344 (-0.2127 to -0.0560)
#>   pi_1 - pi_3: estimate = 0.2041 (0.1453 to 0.2630)
#>   pi_2 - pi_3: estimate = 0.3385 (0.2759 to 0.4011)
#>