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Cognitive and Linguistic Precursors to Early Literacy Achievement inChildren With Specific Language ImpairmentMarjolijn van Weerdenburg a; Ludo Verhoeven a; Hans van Balkom a; Anna Bosman a

a University of Nijmegen,

Online publication date: 12 November 2009

To cite this Article van Weerdenburg, Marjolijn, Verhoeven, Ludo, van Balkom, Hans and Bosman, Anna(2009) 'Cognitiveand Linguistic Precursors to Early Literacy Achievement in Children With Specific Language Impairment', ScientificStudies of Reading, 13: 6, 484 — 507To link to this Article: DOI: 10.1080/10888430903162936URL: http://dx.doi.org/10.1080/10888430903162936

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Cognitive and Linguistic Precursors toEarly Literacy Achievement in Children

With Specific Language Impairment

Marjolijn van Weerdenburg, Ludo Verhoeven,Hans van Balkom, and Anna Bosman

University of Nijmegen

This study investigated the role of cognitive and language skills as predictors of earlyliteracy skills in children with Specific Language Impairment. A range of cognitiveand linguistic skills were assessed in a sample of 137 eight-year-old children withSLI at the beginning of the school year, and 6 months later on word decoding andreading comprehension. The cognitive and linguistic measures revealed four factorsthat were called language, speech, short-term memory, and phonological awareness.Structural equation modeling showed word decoding to be predicted by speech,short-term memory, and phonological awareness, whereas reading comprehensionwas predicted by word decoding skills and short-term memory. It can be concludedthat in children with SLI variations in early word decoding are mostly determined byspeech abilities and short-term memory, and to a lesser extent by phonologicalawareness. Moreover, reading comprehension turns out to be highly dependent onword decoding and short-term memory.

Children with Specific Language Impairment (SLI) fail to develop normal lan-guage despite normal nonverbal intelligence; no known hearing, physical, or emo-tional problems; and an adequate learning environment (Bishop, 1992). Their lan-guage problems are in the domain of producing and/or understanding language.Given that literacy skills are language based, it is likely that children with SLI willbe at risk for literacy problems (Flax et al., 2003; McArthur; Hogben, Edwards,

SCIENTIFIC STUDIES OF READING, 13(6), 484–507Copyright © 2009 Society for the Scientific Study of ReadingISSN: 1088-8438 print / 1532-799X onlineDOI: 10.1080/10888430903162936

Correspondence should be sent to M. W. C. van Weerdenburg, Department of Special Education,Radboud University Nijmegen, P.O. Box 9104, 6500 HE Nijmegen, The Netherlands. E-mail:M.vanWeerdenburg@pwo.ru.nl

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Heath, & Mengler, 2000). Studies have reported that children with early languageimpairment show significantly more literacy problems at follow-up than controls(Aram, Ekelman, & Nation, 1984; Johnson et al., 1999; Nauclér & Magnus-son, 1998; Scarborough & Dobrich, 1990; Snowling, Bishop, & Stothard, 2000;Stothard, Snowling, Bishop, Chipchase, & Kaplan, 1998; Tallal, Allard, Miller, &Curtiss, 1997; Young et al., 2002). In this article, we examine which linguistic andcognitive (e.g., memory) factors play a role in predicting literacy skills in childrenwith SLI.

In children with normal language development, reading can be thought of as aprocess in which several sources of linguistic information are used. The trianglemodel of Plaut, McClelland, Seidenberg, and Patterson (1996) assumes that fluentreaders use both semantic and phonological information during word recognition.According to this connectionist model, there is a “division of labor” between thephonological and semantic pathways, but both pathways are needed to establish suc-cessful word and nonword reading (Plaut et al., 1996). Furthermore, it has beenshown that during the early stages of reading development, reading comprehensionis primarily a function of word reading abilities (Storch & Whitehurst, 2002). Thisinterrelationship between word reading abilities and reading comprehension is dueto the nature of the reading task during the first years of reading instruction; thewords that have to be read are high-frequency words that are within the vocabularyof most children (Whitehurst & Fischel, 2000). Through reading practice, however,word reading and reading comprehension become two entities with reading compre-hension becoming dependent on word reading abilities, on one hand, and the child’sgeneral verbal ability and oral language skills, on the other hand (Storch & White-hurst, 2002; Whitehurst & Fischel, 2000). More precisely, reading comprehensionappears to become dependent on vocabulary knowledge and grammatical skills evenwhen the effects of early word recognition, phoneme sensitivity, and letter knowl-edge are controlled for (Muter, Hulme, Snowling, & Stevenson, 2004).

Given the fact that reading skills may depend on several processes, readingproblems may have different origins. At the word level, the core problem of read-ing disorders is considered to be a deficient level of phonological processing,whereas at the text level problems in reading comprehension are supposed to de-pend on deficiencies at the level of semantics, syntax, and discourse (Snowling,2000). To disentangle the disorders of dyslexia and specific language impairment,Bishop and Snowling (2004) distinguished phonological and nonphonologicallanguage skills. They pointed out that children with “classic dyslexia” have defi-cits only on the phonological dimension and not on the nonphonological dimen-sion, whereas children with SLI may have deficits on both dimensions. Whilereading text, poor word decoding skills may be compensated for by good languageskills in the case of dyslexia (Nation & Snowling, 1998). However, children withSLI have a double deficit in uncovering the meaning of printed text and very fewresources to fall back on.

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Research on children with SLI that focused on linguistic predictors for later lit-eracy problems in these children has been complicated by the fact that SLI is not ahomogeneous disorder (Conti-Ramsden & Botting, 1999; van Weerdenburg, Ver-hoeven, & van Balkom, 2006). Because of this, the relationship between languageand literacy problems was not quite as straightforward as one might expect.Children with SLI showed a range of profiles, reflecting a variety of language-re-lated problems on both receptive as productive domains (Bishop, 1994; Conti-Ramsden, Crutchley, & Botting, 1997). More specifically, children with SLI mayhave phonological, lexical-semantic, morphological, syntactic, and/or processingproblems (Botting & Conti-Ramsden, 2004; Cowan, 1996; Leonard, 1998; Tallal,Miller, Jenkins, & Merzenich, 1997). Different language-related problems can af-fect the reading process at different times, each in its own way. In many studies,the literacy skills of children with SLI appeared to be best predicted by their pho-nological processing abilities (Bird, Bishop, & Freeman, 1995; Briscoe, Bishop, &Norbury, 2001; Catts, 1991, 1993; Larrivee & Catts, 1999; Stackhouse, 2000).However, language predictors for later reading skills changed over time. In somestudies, the best overall predictor for reading in first grade were metalinguisticabilities (e.g., phonological awareness), whereas preschool measures of syntacticand semantic abilities were found to be significantly correlated with reading per-formance after first grade (Magnusson & Nauclér, 1990; Menyuk et al., 1991).Bishop and Adams (1990) found that receptive and expressive semantic-syntacticabilities were the best predictors for reading achievement at age 8. Many of thechildren with SLI in this study were able to decode words accurately yet had poorcomprehension of what they read. Other studies showed that preschool seman-tic-syntactic abilities best predicted word decoding in first grade and reading com-prehension in second grade, but phonological abilities and rapid naming in firstgrade best predicted word decoding in second grade (Catts, 1991, 1993; Catts, Fey,Zhang, & Tomblin, 1999). To conclude, the relationship between language abili-ties and reading achievement in children with SLI cannot be seen as straightfor-ward. This may be caused by the fact that different studies used different measuresand time periods. However, it is also possible that dynamics within the languageand reading development cause a dynamical relationship between the two.

Verbal memory skills play a special role in research on the relationship betweenlanguage and literacy problems. Given the fact that linguistic knowledge andmemory capacity can be seen as highly interdependent, short-term memory taskscan be seen as indirect means of assessing the operation of language-processingmechanisms (MacDonald & Christiansen, 2002). In previous studies, it was foundthat short-term memory is often closely related to phonological processing(Gillam & Van Kleeck, 1996) and of great importance in language (Gillam &Hoffman, 2004) and reading processing (Heath, Hogben, & Clark, 1999; Olofsson& Niedersoe, 1999), whereas verbal short-term memory deficits were found to becharacteristic of disabled readers (Farmer & Klein, 1995; Siegel, 1994). It is im-

486 VAN WEERDENBURG ET AL.

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portant to note that children with SLI have shown deficiencies in verbal short-termmemory that cannot be attributed to the language problem itself (Cowan, 1996;McCarthy & Warrington, 1990). They are often impaired on immediate-memorytasks such as digit span (Archibald & Gathercole, 2006; Hoffman & Gillam,2004). These limitations become particularly apparent when processing load is in-creased (Ellis Weismer, Evans, & Hesketh, 1999; Montgomery, 2000). Further-more, children with SLI show a particular deficit on nonword repetition, which canbe seen as a marker for SLI (Bishop, North, & Donlan, 1996; De Bree, Rispens, &Gerrits, 2007). It is often concluded that the problems in nonword repetition ofchildren with SLI can be attributed to problems in phonological short-term mem-ory (Edwards & Lahey, 1998; Gathercole & Baddeley, 1990). However, whenscores on nonword repetition tasks are adjusted for differences in short-term mem-ory, SLI deficits persist, suggesting that speech-related factors such as prosody,coarticulation, and temporal processing may also play a role (Archibald & Gather-cole, 2007) and that these factors have a substantial effect on literacy development(Gathercole, Tiffany, Briscoe, Thorn, & ALSPAC team, 2005).

The general conclusion from the research so far is that children with languageimpairment are at risk for reading problems and that different cognitive and lin-guistic abilities are predictors for later literacy skills. Verbal short-term memory,phonological, lexical, and syntactical abilities may have predictive value, but therelationship between linguistic abilities and reading abilities in children with SLIis still far from clear. Two major limitations of earlier studies are important toovercome. First, a single task was often used in previous research to represent ageneral measure of the language or reading components under consideration. Therelationships found between language and reading scores on one or two tests werethen used to discuss the relationship between a particular component of language(e.g., the syntactic component) and reading ability in general. Because there ap-peared to be little uniformity in the measures used in the studies to determine thelevel of language and/or reading abilities, generalization from a single test score toa particular ability is questionable in terms of its content validity. Valid measuresof a broad range of predictor variables are needed to draw firm conclusions regard-ing the multidimensional relationships between the various components of cogni-tive, linguistic, and literacy skills. Second, much of the research on predictors ofreading skills in children with SLI has focused on specific domains such as phono-logical and semantic skills or short-term memory. However, because of theintercorrelations between cognitive and linguistic predictors for literacy skills, abroad multidimensional structure of cognitive and linguistic abilities is needed tofully explain literacy skills of children with SLI.

Therefore, in the present study, predictors of the literacy achievement in8-year-old children with SLI in the Netherlands are investigated using a diverserange of cognitive and language measures. In the Netherlands, children attendingmainstream schools start learning to read at the age of 6. During the first year of

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reading instruction, the emphasis is on the structure of the written and spoken lan-guage in order to enhance phonemic abilities and word decoding. Because Dutch isan alphabetic language, acquiring knowledge of graphemes and phonemes is a ba-sic skill for learning to read in Dutch. However, because children with SLI show asevere delay in their language development, formal literacy instruction for thesechildren in the Netherlands starts later. Notwithstanding a strong focus on emerg-ing literacy in kindergarten and first grade, the actual process of learning to readstarts at least 1 year later than age 6. For that reason, in the present study the focuswas on children at the age of 8 who had experienced formal reading instruction forat least 1 year. At this age level, the relationship between cognitive and linguisticabilities as predictor variables of early literacy achievement was examined. Fol-lowing earlier research (Bishop, 2004; Bishop & Snowling, 2004; Leonard, 1998;Montgomery, 2000; Muter et al., 2004) predictor variables were assessed by alarge test battery measuring oral language abilities, speech abilities, short-termmemory skills, and phonological awareness. With respect to literacy achievement,both word decoding and reading comprehension were taken into account. Struc-tural equation modeling was used to provide latent variables with high content va-lidity and to examine structural relationships between predictor and outcome vari-ables. We hypothesized that children’s word decoding could be predicted fromtheir levels of speech abilities, short-term memory skills, and phonological aware-ness. Furthermore, we expected that children’s reading comprehension could bepredicted from their word decoding, on one hand, and oral language abilities, onthe other hand.

METHOD

Participants

All participants were diagnosed with SLI by a multidisciplinary team of specialistsincluding a physician, a psychologist, special educators, and a speech therapist. Achild was diagnosed with SLI when he or she had a severe language impairmentthat was not the direct result of global intellectual, sensory, motor, emotional, orphysical impairments. The nonverbal intelligence of the participants was mea-sured by the Raven Colored Progressive Matrices (standardized M = 5, SD = 2; seevan Bon, 1986, for Dutch norms). The mean score of the children with SLI on thistest was 5.5 (SD = 1.8). Children with hearing problems (> 30 dB hearing loss)were excluded from the present study, and children displaying severe behavioralproblems during testing were also excluded. Parental consent was obtained for allchildren who participated.

All participants were either attending a special school for language- and hear-ing-impaired children (87%) or involved in a special language-remediation pro-

488 VAN WEERDENBURG ET AL.

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gram within a mainstream school (13%). In the Netherlands, there are 30 specialschools for language-impaired children, and 29 of them participated in this study.The participants were randomly selected from the subpopulation of children withSLI between the ages of 8;0 (years; months) and 8;10. The sample consisted of 137children with a mean age of 8;5 (SD = 2 months) at Time 1, of whom 102 (75%)were boys and 35 were girls (25%). Selection of participants from each school wasbased on age, gender, and school size; the more children with SLI in the school orthe remediation program, the larger the percentage of children from that particularschool in the sample. The gender percentages and the distribution in socioeco-nomic backgrounds were representative of the population of 8-year-old childrenenrolled in education for the specifically language-impaired in the Netherlands.

Materials

At Time 1, in the fall of the school year, the participants were tested on a wide vari-ety of language and cognitive skills as presented in Table 1. The children’s lan-guage abilities were evaluated using the Dutch Language Proficiency Test for AllChildren (Taaltoets Alle Kinderen; Verhoeven & Vermeer, 2001), which is a stan-dardized discrete-point test for the assessment of 4- to 10-year-olds and consists ofnine subtests. The subtest of Productive Vocabulary from an earlier version of theLanguage Proficiency Test (Verhoeven & Vermeer, 1986) was also included in thetest battery. All of the subtests have been shown to be reliable with Cronbach’salphas between .90 and .97. The short-term memory of the children was measuredusing two tests from the Dutch version of the Kaufman Assessment Battery forChildren: Word Order and Number Recall (Kaufman & Kaufman, 1983). In addi-tion, the Dutch version of the revised Lindamood Auditory Conceptualization(Lindamood & Lindamood, 1979) was administered. Furthermore, the tasks WordRepetition, Nonword Repetition, and Syllable Series Repetition (Maassen & vander Meulen, 2000) were added to expand the repertoire of words and nonwords tobe articulated.

At Time 2, 6 months later in the spring of the same school year, the childrenwere assessed on literacy skills using tests of word decoding (Brus & Voeten,1973; van den Bos, Lutje Spelberg, Scheepstra, & de Vries, 1994; Verhoeven,1995), and reading comprehension (Verhoeven, 1997). An overview of the(pre)literacy tests administered at Time 2 is presented in Table 2.

Procedure

Assessment took place at two points. The children were tested on cognitive andlanguage measures in the fall of the school year (Time 1). Subsequently, (pre)liter-acy skills were assessed in the spring of the same year (Time 2). Assessment wasdone by trained people at the schools that the children attended. Test administra-

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490

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tion took place in a quiet room outside the classroom. The test instructions andpossible feedback were determined on paper in advance. Children were tested for 3to 5 hr across 1 or 2 months in several test sessions. Session lengths varied on thebasis of children’s attentiveness; sessions were terminated as soon as children ex-hibited attentional lapses.

To answer the research questions about the relationships between the cognitiveand language measures at Time 1 and the (pre)literacy measures at Time 2, the datawere analyzed in four steps. First, missing variable analyses were executed be-cause in all tests, missing data occurred. Listwise deletion of these cases would re-duce the data and have unwanted consequences for the structural equation model-ing analyses. Therefore, the missing variable analyses were executed to test thehypothesis that the missings were completely random using Little’s Missing Com-pletely At Random test (Little & Rubin, 1987). This test revealed χ2(553) =619.93, p = .03, indicating for this sample Missing At Random data. These out-comes on the characteristics of the missing data allowed us to estimate thecovariance matrix by means of a Full Information Maximum Likelihood based onthe saturated model with AMOS (Arbuckle & Wothke, 1999). This covariancematrix formed the basis for further structural equation modeling. The correspond-

492 VAN WEERDENBURG ET AL.

TABLE 2Descriptions of the Time 2 Literacy Tests

Test Description

Word Decoding 1 The child has to read aloud lists of words containing CVC words asfast and accurately as possible in 1 min. The final score for eachlist is the number of words read correctly.

Word Decoding 2 The child has to read aloud a list of words containing CVCC andCCVC words as fast and accurately as possible in 1 min. The finalscore for each list is the number of words read correctly.

lphaWord Decoding 3 The child has to read aloud a list of words containing words with twoor more syllables as fast and accurately as possible in 1 min. Thefinal score for each list is the number of words read correctly.

One Minute Test Decoding The child has to read aloud a list of words ordered from CVC topolysyllabic words as quickly and correctly as possible in 1 min.The final score is the number of correctly read words.

Nonword Decoding The child has to read aloud a list of nonwords ordered from CVC topolysyllabic words as quickly and correctly as possible in 1 min.The final score is the number of correctly read words.

Reading Comprehension The child has to read six short stories. After the reading of a story thechild has to answer 4 multiple-choice questions on paper. The 24questions all are “wh-interrogatives” (i.e., questions starting with“who,” “what,” “where,” or “whom”). The probability of guessingthe correct answer is 25%.

Note. CVC = consonant-vowel-consonant.

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ing correlation matrices are presented in the appendix. Second, the means andstandard deviations of all tests were calculated for the children with SLI and com-pared with information from norm group data. Third, a measurement model wastested as the first of the recommended two-step approach according to Andersonand Gerbing (1988). This measurement model investigated whether the distinctionin factors assumed on the basis of theoretical arguments and earlier research (vanWeerdenburg et al., 2006) was justified. Finally, the causal relationship betweenindependent (i.e., the cognitive and language) variables and dependent (i.e., liter-acy) variables in the structural model was analyzed (Anderson & Gerbing, 1988).

In this study, an initial model was first specified based on theoretical insight. Themodel was then adapted on the basis of modification indices to improve the fit of themodel. Alterations were only made when they were theoretically plausible and eachalteration was added stepwise. Error terms were allowed to correlate in order to im-prove the fit of the model. The goodness of fit of the estimated model was assessedby six indices: chi-square, with degrees of freedom and p value, Adjusted Goodnessof Fit Index (AGFI; Jöreskog & Sörbom, 1996), Normed Fit Index (NFI; Bentler &Bonett, 1980), Comparative Fit Index (CFI; Bentler, 1990), root mean square errorof approximation (RMSEA; Browne & Cudeck, 1993), and standardized root meansquare residual (SRMR; Jöreskog & Sörbom, 1996). The smaller the chi-square rel-ative to the degrees of freedom, the better the fit of the model. A model could beviewed to fit the data acceptably when the ratio of the chi-square to the degrees offreedom was found to be smaller than 2:1, the AGFI and NFI were higher than .80,and the CFI was higher than .95. Furthermore, the RMSEA lower than .06 and theSRMR lower than .10 would provide a close fit (Hu & Bentler, 1999).

RESULTS

Descriptive Statistics

Means and standard deviations are presented for all variables in Table 3. The chil-dren with SLI score below the norm group on all of the language-related tests atTime 1. The results in Table 3 show that the children with SLI are significantly de-layed on all of the cognitive and language measures when compared to typically de-veloping children of the same age. For most language tests it was possible to calcu-late a Z score on the basis of the mean and standard deviation of a norm groupconsisting of 8-year-old children with normal language development. Table 3 showsthat the Z scores were all negative and mostly below –1, indicating a delay that isgreater than 1 standard deviation. Qualitative comparison was possible for the re-maining tests. On the Nonword Repetition task, 8-year-old children with normal lan-guage development are expected to achieve the maximum score of 12. However, the8-year-old children with SLI scored 57% correct (6.78 out of 12). On the ProductiveVocabulary task, the performance of the SLI group was comparable to the lowest

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10% scores for age-related norm group of 8-year-old children (Verhoeven &Vermeer, 1986). On the Syllable Series task, typically developing children of thesame age are expected to achieve the maximum score of 11. The mean score of thechildren with SLI was 75% correct (8.24, SD = 2.35). Finally, on Word Repetition,the maximum score was 10 words to be repeated correctly. The average score of thechildren with SLI was 76% (M = 7.5, SD = 2.10). In sum, quantitative and qualitative

494 VAN WEERDENBURG ET AL.

TABLE 3Differences Between Group With Specific Language Impairment (SLI) and Respective Norm

Group on Language Tests at Time 1 and Literacy Tests at Time 2

Numberof Items

SLI Norm

Test N M SD M SD Za

Articulation 45 137 40.61 5.32 44.85 0.50 —b

Definition 45 137 15.98 7.47 27.90 5.98 –1.99Function Words 42 137 36.56 3.89 39.13 2.50 –1.03K-ABC Number Recall 19 137 6.07 2.37 10.00 3.00 –1.31K-ABC Word Order 20 137 6.30 2.89 10.00 3.00 –1.23LAC-r 1a 10 135 8.57 2.91 9.80 0.99 –1.24LAC-r 1b 6 135 4.38 1.90 5.13 0.93 –0.81LAC-r 2 12 135 7.44 3.61 9.00 2.53 –0.62Morphology 24 137 15.70 5.20 21.34 3.00 –1.88Receptive Vocabulary 96 137 70.93 12.59 83.65 8.07 –1.58Story Comprehension 24 137 17.83 3.66 20.53 3.32 –0.81Syntactic Patterns 42 137 35.12 4.96 39.97 1.80 –2.69

TestNumberof Items N M SD Qualitative Comparisonc

Nonword Repetition 12 136 6.78 2.70 mean performance = 57%Productive Vocabulary 60 136 37.90 8.60 lowest 10% of norm scoresSyllable Series Rep. 11 136 8.24 2.35 mean performance = 75%Word Repetition 10 136 7.55 2.10 mean performance = 76%Literacy Test T2

Word Decoding CVC 150 126 51.40 24.15 lowest 10% of norm scoresWord Decoding CCVCC 150 116 43.66 24.10 lowest 10% of norm scoresWord Decoding Poly. 120 111 33.42 20.84 lowest 10% of norm scoresOMT Word Decoding 116 112 31.48 18.50 lowest 1.5 % of norm scoresNonword Decoding 116 112 26.68 19.24 lowest 20% of norm scoresReading Comprehension 130 106 103.88 12.17 lowest 10% of norm scores

Note. ABC = Assessment Battery for Children; LAC-r = Lindamood Auditory Conceptualizationrevised; CVC = consonant-vowel-consonant; OMT = One Minute Test.

aZ scores were calculated using (Mnorm - MSLI) / SDnorm.bNorm group distribution of the Articulation test was not normal (i.e., showed a ceiling effect) and

therefore, the Z scores could not be calculated.cQualitative Comparison was done when Z scores could not be calculated because of missing stan-

dard deviations of norm data.

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norm group comparisons show that the children with SLI are severely delayed on allcognitive and linguistic tests that are used in this study.

At Time 2, scores of the children with SLI on Word Decoding 1, 2, and 3 werecomparable to the lowest percentile (0–10%) of the norm group distribution ofchildren at the same age (Verhoeven, 1995) as can be seen in Table 3. The numberof children scoring above mean (i.e., falling above the median of the norm distri-bution) was between 39 (on Word Decoding 1) and 46 (on Word Decoding 2 and3). Scores on the One Minute Test (OMT) Decoding fell in the lowest 1.5% andscores on Nonword Decoding fell in the lowest 20% of the norm group distributionof children at the same age (van den Bos et al., 1994). On the OMT Decoding test,34 children with SLI had reading level above mean (i.e., falling above the medianof the norm distribution) and on the Nonword Decoding test the number of chil-dren with sufficient reading level was 41. Finally, scores on Reading Comprehen-sion were comparable to the lowest 10% of the norm distribution of children with anormal language development, but with an age that was one year below the one ofthe 8-year-old group with SLI (Verhoeven, 1997).

Measurement Models

A measurement model was tested as the first of the recommended two-step ap-proach according to Anderson and Gerbing (1988) to investigate whether the fac-tor structure proposed on the basis of theory (Bishop, 2004; Bishop & Snowling,2004; Leonard, 1998; Montgomery, 2000; Muter et al., 2004) and a previous studyon the same sample (van Weerdenburg et al., 2006) was justified. This measure-ment model provided a close fit for the data of the children with SLI in the presentsample. In this model, the cognitive and language variables represented four fac-tors that were labeled language, short-term memory, speech, and phonologicalawareness. For a description of the observed variables, see Table 1. The first fac-tor, language, was defined by tasks measuring the understanding and production ofwords and sentences; Receptive and Productive Vocabulary, Story Comprehen-sion, Definition, Morphology, Function Words, and Syntactic Patterns. The sec-ond factor, short-term memory, was defined by tasks assessing the recall of wordlists by pointing to pictures (in the test Word Order) or the verbal recall of Num-bers (Number Recall). The third factor, speech, was defined by tasks in which thecommon ability was to correctly repeat nonwords (Nonword Repetition and Sylla-ble Series Repetition) and words (Word Repetition and Articulation). Nonwordrepetition is often seen as a measure of phonological short-term memory (Bishopet al., 1996; Edwards & Lahey, 1998; Gathercole & Baddeley, 1990) and the WordRepetition task contained polysyllabic words that may have sound like nonwordsto the children with SLI. Nevertheless, testing the hypothesis that these tasks weremeasures of short-term memory provided a worse fit of the model. The fourth fac-tor, phonological awareness, was defined by three tasks from the Lindamood Au-

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ditory Conceptualization revised tasks (see Table 1). This factor measured theability to represent the number, sameness of difference, and order of orally pre-sented phonemes. The phonemes were either presented as separated units in a row(/b/ /b/ /z/) or in a nonword (/vaps/ and /vops/).

The literacy factors at Time 2 were word decoding and reading comprehension.The factor word decoding was defined by five measures: Word Decoding 1, 2, and3; OMT Decoding; and Nonword Decoding. The factor reading comprehensionwas defined by a single observed variable Reading Comprehension by fixing theerror variance of this observed variable to equal its reliability (.90).

For the present sample, the measurement model had reasonable fit indices (seeTable 4, Model 1). To improve the fit of the model, residual variances of pairs ofvariables within the same latent variable were also allowed to covary. This wasdone 12 times between Function Words and Syntactic Patterns; between Produc-tive Vocabulary and Receptive Vocabulary; between Productive Vocabulary, andDefinition; between OMT Decoding and Nonword Decoding; between NonwordRepetition and Syllable Series Repetition; between Syntactic Patterns and Recep-tive Vocabulary; between Word Decoding 1 and 2; between Receptive Vocabu-lary and Function Words; between Story Comprehension and Syntactic Patterns;between Story Comprehension and Definition, between Decoding 3 and NonwordDecoding; and finally between Definition and Function Words. This resulted in anacceptable model, χ2(188) = 310, p < .001; AGFI = .77, NFI = .88, CFI = .95,RMSEA = .07, CFI = .89, and SRMR = .12 (see Table 4, Model 2). The independ-ent predictors were allowed to correlate, and Table 5 shows that most correlationswere moderate but significant with p < .05.

Predictors of Reading Abilities

The relationship between the latent measures of language skills at Time 1 and liter-acy skills at Time 2 was investigated by adding the latent variables word decoding

496 VAN WEERDENBURG ET AL.

TABLE 4Goodness of Fit Statistics for Measurement and Structural Models

Model 2 df p AGFI NFI CFI RMSEA SRMR

1 Measurement model(no adjustments)

466 200 < .001 .69 .82 .89 .10 .13

2 Measurement model(with adjustments)

310 188 < .001 .77 .88 .95 .07 .12

3 SEM (withadjustments)

248 183 .001 .81 .91 .97 .07 .07

Note. AGFI = Adjusted Goodness of Fit Index; NFI = Normed Fit Index; CFI = Comparative FitIndex; RMSEA = root mean square error of approximation; SRMR = standardized root mean square re-sidual; SEM = structural equation model.

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and reading comprehension to the model with the four latent variables derivedfrom the measurement model (i.e., language, short-term memory, speech, andphonological awareness). In this model all possible paths from the latent measuresof language skills to the outcome measures of reading ability were included. Theresulting simplified model is shown in Figure 1. Nonsignificant paths from inde-pendent to dependent latent variables, error covariances, and the error terms ofeach observed variable are not presented in the model for reasons of simplification.The fit measures of this final model (see Table 4, Model 3) indicated a reasonablefit: χ2(183) = 248, p < .001; AGFI = .81, NFI = .91, CFI = .97, RMSEA = .07, andSRMR = .07.

In Figure 1 it can be seen that word decoding is best predicted by the factorspeech (standardized regression coefficient = .21), followed by short-term mem-ory (standardized regression coefficient = .39) and phonological awareness (stan-dardized regression coefficient = .21). There is no significant path from the factorlanguage to word decoding. Furthermore, it can be seen that reading comprehen-sion is predicted by word decoding (standardized regression coefficient = .42) andby short-term memory (standardized regression coefficient = .32). The factorsphonological awareness, speech, and language did not have significant relation-ships with reading comprehension.

CONCLUSIONS AND DISCUSSION

The general purpose of this study was to explore the role of cognitive and linguisticfactors as predictors of the early literacy skills of children with SLI. The perfor-mance on cognitive and language tests of 8-year-old children with SLI were com-pared were first compared to the normative scores of typically developing childrenof the same age. The results showed that the children with SLI were performingpoorly on all tests with delays usually greater than 1 standard deviation. Severe de-lays were also found on the literacy tests. All (non)word-decoding scores werecomparable to the lowest end of a norm distribution of children with normal lan-

EARLY LITERACY ACHIEVEMENT 497

TABLE 5Correlations Among Latent Language Abilities in the Structural Equation

Model

1 2 3 4

1. Phonological awareness —2. Speech .39 —3. Short-term memory ns .44 —4. Language .50 .50 .43 —

Note. All significant correlations have p < .05.

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guage development of the same age and the reading comprehension scores werecomparable to the lowest end of a norm distribution of younger children with nor-mal language development. It can be concluded that the children with SLI in thisstudy have a severe delay not only in language skills but also in literacy skills. Thisis consistent with the results of earlier studies on the relationship between lan-

498 VAN WEERDENBURG ET AL.

FIGURE 1 Structural equation model of the relationship between cognitive and languagefactors at Time 1 (M age = 8;4, SD = 2 months) and Word Decoding and Reading Comprehen-sion at Time 2 (M age = 8;10, SD = 2 months). Note. Ovals represent latent variables and rectan-gles represent observed variables. All significant path coefficients have p < .05. χ2(183) =248.297, p = .001; AGFI = .810, NFI = .906, CFI = .97, RMSEA = .051, and SRMR = .0728.

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guage and reading deficits in children with language impairments (for reviews, seeLarney, 2002; Schachter, 1996). Most of the previous studies dealt with English,which has a highly irregular orthography with many inconsistencies and complex-ities. It is important to note that literacy impairments among children with SLI alsoapply to the Dutch orthography, which can be considered much more consistentthan English.

The testing of a measurement model revealed that the cognitive and languageabilities of the children with SLI are multidimensional and that they can be repre-sented by four correlated factors: language, speech, short-term memory, and pho-nological awareness. Lexical and syntactic skills were underlying the factor lan-guage and the factor speech was comprised of articulation and nonword repetitiontasks. Furthermore, short-term memory consisted of measures in which the childhad to repeat sequences of words (verbally or by pointing). Finally, phonologicalawareness consisted of purely receptive tasks in which the child had to representthe number, sameness or difference, and order of phonemes by placing coloredblocks in a particular order. These results are partly in accordance with Hayiou-Thomas et al. (2006). Their factor analyses on the data of 556 twin pairs at the ageof 4½ years assessed with an extensive battery of verbal and nonverbal measuressuggested two factors; the Articulation factor consisted of speech and nonwordrepetition tasks, and all other measures were assembled in the Language factor.The speech factor of our study is comparable to the Articulation factor of Hayiou-Thomas et al. Apparently, nonword repetition reflects phonological output pro-cesses more than phonological working memory (cf. Snowling, Chiat, & Hulme,1991). However, in contrast with the two-factorial model of Hayiou-Thomas et al.,our results suggest a four-factorial model. This is not because their children wereyounger (4½ years in stead of 8½ years) because a four-factorial model is found inDutch children with SLI at the age of 4, 6, and 8 years (van Daal, Verhoeven, &van Balkom, 2004; van Weerdenburg et al., 2006). It may have to do with differ-ences in measures and with the fact that the sample of Hayiou-Thomas et al. in-cluded English-speaking children with normal language development and childrenwith language difficulties, whereas our sample only consisted of children withSLI.

The structural equation model testing the relationship between these four factorsand children’s literacy achievement 6 months later showed that for word decodingthe best predictor was speech, followed by short-term memory and phonologicalawareness. This result is fully in line with our predictions. However, it is interestingto note that the impact of speech and short-term memory on word decoding is greaterthan that of phonological awareness. The importance of speech abilities derivesfrom the idea that word-decoding abilities are highly dependent on the quality ofphonological representations of words children have learned over the years. Onemay argue that the quality of lexical representations is crucial for fast lexical re-trieval of words. Indeed, Catts (1993) found that children who lack a full use of the

EARLY LITERACY ACHIEVEMENT 499

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normal range of phonemic contrasts may encounter difficulties with word decodingtasks. In a similar vein, Snowling et al. (2000) found that students with expressivephonological problems at preschool age performed less well on word decoding andphonological awareness tasks in later years. The importance of short-term memorypoints to the fact that word decoding can take place only if the phonological infor-mation underlying orthographic word patterns can be briefly and statically retained(Baddeley, Gathercole, & Papagno, 1998). It might well be the case that the childrenwith SLI are just not efficient in the inner rehearsal aspect, which allows the phono-logical information needed for the process of language comprehension to be retainedlonger in memory (cf. Hoffman & Gillam, 2004).

Reading comprehension was predicted by word decoding and short-term mem-ory. The fact that reading comprehension is predicted by word decoding is consis-tent with the lexical quality hypothesis that sees reading skill depending on the pre-cision of a reader’s representation of orthography, phonology, morphology, andmeaning (Perfetti & Hart, 2001; Verhoeven & Perfetti, 2008). Word decoding orthe accurate and fast retrieval of the phonological code for written word forms iscommonly assumed to play a central role in reading comprehension and the devel-opment of such. More specifically, the automatization of word decoding skills andattainment of fluent reading levels frees mental resources for closer considerationof the meaning of a text and can thus be regarded essential for the development oftext comprehension (Perfetti, 1992; Samuels, 1994; Stanovich, 2000). The factthat in the present study reading comprehension is predicted by word decoding andnot by language skills can at least partly be explained by the fact that the childrenunder investigation can be regarded as beginning readers. Previous research hasshown that the role of word decoding in the explanation of reading comprehensiontends to be large for beginning readers, whereas the role of language abilities isfound to be more prominent for proficient readers (cf. Carver, 1993; Chen &Vellutino, 1997). From the results of the present study, it can be concluded thatthere is a relationship between language and reading comprehension, because theindividual measures comprising the language composite show significant correla-tions with reading comprehension (see appendix). However, this relationship ismediated entirely through short-term memory and indirectly through the other fac-tors by means of their predictive value for word decoding.

It is also important to highlight the important role of short-term memory as ad-ditional predictor of reading comprehension in children with SLI. Short-termmemory can be seen as crucial in holding phonological clause units ready for fur-ther processing of meaning integration. The need to keep the phonological repre-sentation of a sentence active to the end of a clause can be seen as mandatory forreading comprehension. Given abundant problems with holding phonological in-formation, short-term memory for phonological information in many childrenwith SLI may pose a critical bottleneck for the development of both decoding andreading comprehension skills (cf. Hoffman & Gillam, 2004).

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In sum, the results of this study emphasize the importance of taking into ac-count the multifactorial character of the problems seen in children with SLI. Dif-ferent aspects of both language and cognitive abilities influence later literacy skillsin an interactive way. Thus, assessing all relevant domains is necessary for gettinga clear picture of the factors that play a role in the reading process of children withSLI. Of course the present study has several limitations. One is the period under in-vestigation. It should be acknowledged that at Time 1, in the fall of the school year,only linguistic and cognitive measures were assessed and not reading skills. Thiswas done because we did not want to overburden the children with too many tests.Given this limitation we do not know how the early development of reading skillscould be predicted from cognitive and linguistic measures. However, it should bementioned that the literacy skills of the children at Time 1 would probably havebeen highly correlated to the literacy scores at Time 2 and there is no reason to be-lieve that the predictor measures would have pointed in different directions. A fur-ther limitation concerns the selection of predictor measures in the present study. Amore thorough analysis of children’s auditory processing could have been made(see Corriveau, Pasquini, & Goswami, 2007). Likewise, instruments assessing as-pects of executive function could have been included (see Gathercole et al., 2005).Another limitation is that it examines the variation of literacy skills in childrenwith SLI only. Therefore, we do not know to what extent the patterns found areunique to the population being studied. In future studies, a comparison of cognitiveand linguistic predictors of early literacy abilities in different subpopulations maygive a better answer to this question.

Clinical Implications

On the basis of the results of the present study, it can be concluded that multidi-mensional and interactive processes among distinguishable cognitive and linguis-tic abilities are present within children with SLI in the early stages of learning toread. In children with normal language development, literacy development canalso be conceptualized as an interactive process with interplay between phonologi-cal and semantic resources and the ability to use context to activate semanticknowledge. However, in typically developing children, cognitive and linguisticskills all serve to support the reading process. When one process is insufficient todecode a word, another may thus take over (Snowling, 2000). For children withSLI, however, the presence of more than one deficit may limit the ability to com-pensate and cause the process of learning to read to stagnate (Bishop & Snowling,2004). For purposes of clinical practice, therefore, not only the severity of the de-lay but also the type of the cognitive or language deficit should be carefullymapped. The present study makes clear that phonological aspects of short-termmemory and speech-related abilities can be seen as essential prerequisites for liter-

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acy development in children with SLI and such skills might usefully be assessedand targeted in interventions if they appear to be deficient.

ACKNOWLEDGMENTS

This research was partially supported by Viataal, St. Michielsgestel, the InstituteSt. Marie, Centre for Assessment and Treatment of Children and Adolescents withAuditory and/or Communicative Disabilities, Eindhoven, and the Mgr. J.C. vanOverbeek Foundation, Den Bosch, all situated in the Netherlands. Special appreci-ation is expressed to the children who participated, their parents, teachers, and cli-nicians of the participating schools.

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