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年龄与语素平均话语长度之间的关系。

The relation between age and mean length of utterance in morphemes.

作者信息

Miller J F, Chapman R S

出版信息

J Speech Hear Res. 1981 Jun;24(2):154-61. doi: 10.1044/jshr.2402.154.

DOI:10.1044/jshr.2402.154
PMID:7265928
Abstract

The relationship between child age and mean length of utterance measured in morphemes (MLU) was studied in a sample of 123 middle- to upper-middle-class midwestern children, aged 17 to 59 months, conversing with mothers in free play. A significant correlation was found between age and MLU: r = .88. Age accounted for 78% of the variance when MLU was regressed on age; and MLU accounted for 77% of the variance when age was regressed on MLU. Significant nonlinear components accounted only for an additional 1% and 3% (respectively) of the variance. Ranges within one standard deviation (SD) were estimated for predicted MLUs and derived for predicted ages on the basis of linear regression. MLU increased at an average rate of 1.2 morphemes per year; predicted variability in predicted MLU increased with age. These findings can play a useful role in three activities when the children studied are from populations similar to the one sampled here, and MLUs are obtained in the same way. They can aid in (1) finding children whose development of productive syntax requires further diagnostic evaluation; (2) finding children at a particular linguistic stage quickly; and (3) predicting the age most likely to be associated with a given MLU. The substitution of local MLU norms, sampled from the population and ages of clinical interest, can further sharpen these evaluations.

摘要

在123名年龄在17至59个月之间的中西部中上层阶级儿童样本中,研究了儿童年龄与以语素衡量的平均语句长度(MLU)之间的关系。这些儿童在自由玩耍时与母亲交谈。研究发现年龄与MLU之间存在显著相关性:r = 0.88。当MLU对年龄进行回归时,年龄解释了78%的方差;当年龄对MLU进行回归时,MLU解释了77%的方差。显著的非线性成分仅分别额外解释了1%和3%的方差。根据线性回归估计了预测MLU在一个标准差(SD)范围内的值,并得出了预测年龄的值。MLU平均每年增加1.2个语素;预测MLU的预测变异性随年龄增加。当所研究的儿童来自与这里抽样的人群相似的群体,并且以相同方式获得MLU时,这些发现可以在三项活动中发挥有用作用。它们可以帮助(1)找出其生成性句法发展需要进一步诊断评估的儿童;(2)快速找出处于特定语言阶段的儿童;(3)预测最可能与给定MLU相关的年龄。用从临床感兴趣的人群和年龄中抽样得到的当地MLU规范进行替换,可以进一步提高这些评估的准确性。

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