This paper describes a plausible values imputation approach for deriving population scores on several language proficiency domains. The approach harnessed a multi-dimensional item response analysis combining student responses, rater judgements and student background variables. The target population was grade one and grade two primary school students enrolled in the Hong Kong schooling system. The raters were local teachers of English employed within the sampled schools. The primary objective of this research was to impute plausible values for data where no data was provided or where rater data was deemed suspect. By necessity, a secondary objective of this study was to establish rules for justly excluding particular data on the basis of questionable validity. Surveys such as TIMSS, PISA and NAEP have used such 'plausible value' methodologies to account for incomplete test designs and person non-response. The point of difference between this study and other similar studies was the use of item response theory (in particular plausible values) to replace and quantify the impact of potentially invalid rater judgements in a large-scale educational survey.