checkRd: (-1) lcpm.Rd:52: Lost braces; missing escapes or markup?
    52 | \code{lcpm} provides the maximum likelihood estimate for ordinal outcomes (J>2 categories) and a Generalized Linear Model (GLM) with the log link without the assumption of proportionality. That is, lcpm determines the MLE for log[P(y <= j)]= cut_j + X beta_j subject to [cut_{j-1} + X beta_{j-1} <= cut_j + X beta_j] and [cut_j + X beta_j <=0]. This implementation uses \code{\link{constrOptim}}  to determine the MLE and so the results account for the restricted parameter space.
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checkRd: (-1) lcpm.Rd:52: Lost braces; missing escapes or markup?
    52 | \code{lcpm} provides the maximum likelihood estimate for ordinal outcomes (J>2 categories) and a Generalized Linear Model (GLM) with the log link without the assumption of proportionality. That is, lcpm determines the MLE for log[P(y <= j)]= cut_j + X beta_j subject to [cut_{j-1} + X beta_{j-1} <= cut_j + X beta_j] and [cut_j + X beta_j <=0]. This implementation uses \code{\link{constrOptim}}  to determine the MLE and so the results account for the restricted parameter space.
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checkRd: (-1) ppm.Rd:51: Lost braces; missing escapes or markup?
    51 | \code{ppm} provides the maximum likelihood estimate for ordinal outcomes (J>2 categories) and a Generalized Linear Model with the log link with the assumption of proportionality. That is, ppm determines the MLE for log[P(y <= j)]= cut_j + X beta subject to [cut_{j-1} <= cut_j ] and [cut_j + X beta <=0]. This implementation uses \code{\link{constrOptim}} to determine the MLE and so the results should correctly account for the restricted parameter space. A proposed test for proportionality is included in \code{\link{lcpm}}.
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