Behavior Research Methods, Instruments, & Computers1996,28 (4),537-555

A set of 254 Snodgrass-Vanderwart picturesstandardized for Spanish:

Norms for name agreement, image agreement,familiarity, and visual complexity

M.CARMEN SANFELIU and ANGEL FERNANDEZUniversidad de Salamanca, Salamanca, Spain

The Snodgrass and Vanderwart (1980)picture set was standardized for a Spanish sample (N = 261).The present article shows the main results, but more explicitly, it shows the differences between En- .glish and Spanish data. This evidence justifies the statement that normative data of cognitive stimulicannot be taken into another language directly, because object names that are very common in one lan­guage may not be so in another, or objects that have a specific name in one language may have a genericname in another, and so on. Finally, because of the potential usefulness of the data for bilingualism stud­ies, the Spanish data are presented jointly with the English data.

Often, cognitive research requires that the material tobe processed be selected according to very specific,experimenter-defined characteristics. One way in whichthat selection can be effectively achieved is through theuse ofnormative databases. Norms for verbal material havebeen in use for many years (see Bradshaw, 1984, andBrown, 1976, for reviews of early work) and continue tobe used (see, e.g., Benjafield & Muckenheim, 1989; Er­ickson, Gaffney, & Heath, 1987; Ferraro & Kellas, 1990;Gibson & Watkins, 1988; Graff & Williams, 1987; Wil­son, 1988).

Fewer normative data, however, have been collectedfor pictorial stimuli. Until the last decade it was difficultto establish comparisons among studies in which picto­rial stimuli were used due to the fact that different picturesor drawings were utilized in each study. This lack ofstim­ulus homogeneity often resulted in a real difficulty forcomparing and interpreting results. A turning point was thepublication of Snodgrass and Vanderwart's (1980) well­known paper, which provided a thorough report of nor­mative data for a set of260 line drawings. Snodgrass andVanderwart attended to dimensions such as name, famil­iarity, visual complexity, and agreement between mentalimages and pictures.

This standardized set of drawings was soon used in ex­periments in which processing differences between words

The authors would like to thank Joan Gay Snodgrass for sending theset of pictures, as well as for her permission to publish the data fromSnodgrass and Vanderwart (1980). We would also like to thank Emi­liano Diez for his work in the design and implementation of the com­puter program, and Olga Fernandez, Ildefonso Mendez, Emilio 1.Martin, and Marcos Perez for their help in the data collection. Corre­spondence should be addressed to M. C. Sanfeliu, Departamento dePsicologia Basica, Psicobiologia y Metodologia, Facultad de Psicologia,Universidad de Salamanca, Avda. de la Merced, 109-113,37005, Sala­manca, Spain (e-mail: mcsanfe@gugu.usal.es).

and pictures were investigated, both in semantic and epi­sodic memory tasks. The topic ofword-picture differencesis central in modern cognitive research and has led psy­chologists to the discovery of important facts and to theelaboration of sophisticated theories. For example, it hasbeen found that naming time is shorter for words than forpictures, although categorization is faster for pictures thanfor words (Potter & Faulconer, 1975; Snodgrass & McCul­lough, 1986, Vanderwart, 1984). Another important prob­lem concerning word-picture differences is the picture su­periority effect in memory tasks. The discovery of thisphenomenon stimulated the development oftheoretical ac­counts of intervening memory structures and processes,such as the dual coding hypothesis (Paivio, 1971, 1983)and the sensory-semantic model (Nelson, Reed, &Walling, 1976). Both approaches have shown considerablemerit in the attempt to account for recall and recognitiondata (Mantyla, 1986; see Bajo & Canas, 1988a, 1988b, forreviews). However, several discrepancies-like those aris­ing from the utilization of different materials-need to beresolved. The use of standardized materials can contributeto the reduction ofthe disparities among experimental pro­cedures and, in that way,provide a firmer basis for the com­parison ofboth results and theoretical accounts.

Another area in which the use of standardized pictorialmaterials has proven to be important is perceptual identi­fication and recognition. Examples ofprogress in this areaare found in work on recognition thresholds (Kroll & Pot­ter, 1984; Snodgrass, 1984; Snodgrass & Corwin, 1988;Snodgrass & Poster, 1992) and on recognition of objectand non-object drawings (Mou, Anderson, Vaughan, &Rouse, 1989). Finally, drawings have been used increas­ingly in experiments aimed at the study of implicit mem­ory. Recent work with pictures has demonstrated that theeffects found with verbal materials are readily replicablewhen drawings are used. Snodgrass and Vanderwart's

537 Copyright 1996 Psychonomic Society, Inc.

538 SANFELIU AND FERNANDEZ

(1980) original set of standardized drawings has beenmodified to build series with eight levels of increasingfragmentation (Snodgrass, Smith, Feenan, & Corwin,1987). The series have been used in experiments in whichprior exposure can prime both word and picture frag­ments (Feenan & Snodgrass, 1990; Hirshman, Snodgrass,Mindes, & Feenan, 1990; Snodgrass & Feenan, 1990;Snodgrass & Surprenant, 1989). This line ofresearch hasrecently been extended by the construction ofa series ofgradually degraded verbal material consisting ofeight lev­els of increasing fragmentation ofthe names of the Snod­grass and Vanderwartpictures (Snodgrass & Poster, 1992).

This review is far from exhaustive, but it clearly sup­ports the view that the standardization of pictorial stim­uli, such as the set of Snodgrass and Vanderwart (1980)drawings, has had an unquestionably positive effect onresearch devoted to the study ofpicture processing. At thesame time, further work is needed to expand the originalwork on picture standardization to other contexts becauseofnorm generalization difficulties. One case in which thatwork is necessary is the collection of normative data in dif­ferent linguistic and sociocultural contexts. Objects thatare common in a given culture might be less common inanother culture; pictures that evoke a very specific andconcrete name in English might evoke a more generalterm in another language; or images that show a high levelof name agreement for English speakers might showhigher variability in a different community of speakers.Because of these and related problems, a serious effortshould be devoted to the empirical validation ofall kindsof normative data with appropriate population samples.The research reported in this paper is part ofan effort tocollect adequate normative data for pictorial stimuli inthe Spanish-speaking population.

Several studies have focused on the task of obtainingnormative data for verbal stimuli in Spanish. The firstquantitative report was made available by Juilland andChang-Rodriguez (1964), who developed a frequencyindex for Spanish words. In more recent years, other re­searchers have presented additional normative data forverbal material (see Dasi, 1986, for a listing and review ofavailable norms). Special mention has to be made to thework of Algarabel and his colleagues at the Universidadde Valencia (Algarabel, Ruiz, & Sanmartin, 1988; Algar­abel, Sanmartin, Garcia, & Espert, 1986; Pascual, Gotor,Miralles, & Algarabel, 1979). They have made a very sys­tematic attempt to collect norms for words, attending toseveral dimensions (category membership, free associa­tion, number ofsyllables, etc.). Furthermore, they have as­sembled the data in a single, 16,000-word computerizeddatabase, the University ofValencia's WordPool (UVWP),that allows for easy consultation (Algarabel et aI., 1988).

No comparable approach has been applied to pictorialstimuli. In order to provide researchers with normative dataon pictures that are appropriate for Spanish-speakingsubjects, a study was conducted in which the stimuli were254 line drawings from the set first used by Snodgrassand Vanderwart (1980). Closely following their procedure,norms for name agreement, familiarity, visual complex-

ity,image agreement, picture-name agreement, and imagevariability were collected.

METHOD

SubjectsA total of261 students from introductory courses in psychology

from the Universidad de Salamanca participated in the study. Dif­ferent subjects participated in each of the six tasks. There were 62in the name agreement task, 55 in the image agreement task, 51 inthe familiarity task, 59 in the complexity task, and 19 and 15 in thesubsidiary tasks of picture-name agreement and image variabilityagreement, respectively. All the subjects were native Spanishspeakers and participated voluntarily as a course activity. Each ses­sion was run in small groups of up to 5 people.

MaterialsThe stimuli were a set of 254 pictures from Snodgrass and Van­

derwart (1980). A digitized version ofthe drawings was used to pre­sent them on a Macintosh SE/30computer screen. Three ofthe tasksrequired auditory presentation ofnames. These auditory stimuli weredigitized, stored in the computer, and presented through a loud­speaker. A custom-made program controlled presentation ofvisualand auditory stimuli in all the tasks.

ProcedureThe procedure closely followed the steps described by Snodgrass

and Vanderwart (1980), both in terms ofthe tasks performed and inthe way the tasks were done. The only difference was that in our studyall the stimulus presentation processes were controlled by a micro­computer. Drawings were randomly presented in the center of thescreen inside a 95 X 130 rom frame over a white background. Soundswere amplified to a perfectly audible level. Subjects sat in a quiet roomin front ofthe computer screen at a distance ofapproximately 1.5 m.

The six different tasks were run in a similar way. At the beginningof every session in each task, subjects were read the instructionsand encouraged to answer carefully and consistently. They weregiven individual answer sheets and instructed to respond to everydrawing. The total amount of time was between 40 min for thequicker task and I h for the slower one, with one or two 3-min breaksdepending on the length of the session. Each picture was presentedfor a period of 4 sec, and there was a 4-sec interstimulus delay dur­ing which subjects had to rate the stimulus according to the in­structions for each task.

In the name agreement task, subjects had to identify the drawingwith the first name that came to mind and write the name on the an­swer sheet. If that was not possible, they had to indicate whether thereason was "don't know object" (DKO), "don't know name" (DKN),or "tip of the tongue" (TOT).

In the familiarity task, subjects had to rate the degree to whichthe object represented in the drawing was familiar to them, basingtheir rating on the frequency with which they came across the ob­ject in everyday life. Their answer to each item was a whole num­ber from a 5-point rating scale (I = a very unfamiliar object, 5 =a very familiar object).

The visual complexity task required the subjects to rate the com­plexity of each drawing, rather than the complexity of the object itrepresented. They also had to provide ratings from a 5-point scale(I = drawing very simple, 5 = drawing very complex).

In the image agreement task, subjects were asked to estimate howsimilar each picture was to a mental image of an object they hadpreviously been asked to form. First, while the screen remainedblack, they heard the name of the object through the loudspeaker,and had 3 sec to form a mental image of it. After that, a picture ofthe object was presented on the screen. From that moment they had4 sec to rate the degree of agreement between their mental imageand the picture (I = low agreement, 5 = high agreement). If theycould form no image, they were instructed to write the letters NI,

and if the formed image corresponded to a different object, theyhad to write the letters DO. The name used with each picture wasthe most common name given to the object in the name agreementtask. Nine ofthe drawings were excluded from this and the next twotasks because they failed to reach a 30% level of agreement in thename agreement task. The level of agreement was low for severaldifferent reasons, such as the use of a category label instead of theconcrete object name, confusion with similar-looking objects, ob­ject not known, and so on.

In the picture-name agreement task, subjects listened to the nameand saw the picture at the same time. After each picture-name pre­sentation, subjects had 4 sec to rate, on a 5-point scale, how closelythe picture matched the way they expected the named object tolook. In the last task, image variability, subjects listened to the namealone and then they had to indicate, using a 5-point scale (1 = fewimages, 5 = many images), whether the name evoked few or manydifferent images.

RESULTS AND DISCUSSION

A summary of the rating data obtained from our sam­ples ofSpanish-speaking subjects is presented in Appen­dix A. Blank responses were not taken into account inthe computation ofthe ratings. Toallow for easy referenceand data comparison, entries are listed according to theidentifying numbers originally assigned to each drawingby Snodgrass and Vanderwart (1980). For each picture,the following information is presented: (1) most frequentname given in Spanish; (2) most frequent name in Eng­lish; (3) two measures ofname agreement, the statistic Hand the percentage of subjects producing the most com­mon name; and (4) the means and standard deviations forimage agreement, familiarity, visual complexity, picture­name agreement, and image variability. Along with theratings obtained with Spanish-speaking subjects, Appen­dix A also presents the data obtained by Snodgrass andVanderwart with their English-speaking subjects. Thisgrouping and presentation of the data allows for easycomparison ofratings given by the two samples to the samedrawing in each task. Appendix B lists the alternate namesgivento each drawing, with an indicationoftheir frequency.

Table I presents summary statistics for the followingindices: H (reflecting name agreement), percentage, imageagreement, familiarity, and complexity. The table con-

PICTURES STANDARDIZED FOR SPANISH 539

tains the summary for both the Spanish-speaking samplesand the English-speaking samples reported by Snodgrassand Vanderwart (1980). Although H and percentage aretwo measures of name agreement, following Snodgrassand Vanderwart's arguments, 1 we will use H as the mea­sure ofname agreement. Separate t tests were conductedto compare the ratings given in each of these dimensionsby Spanish speakers and English speakers in response tothe 254 drawings that were common to both studies. Therewere small but significant differences for familiarity andcomplexity. In the English-speaking sample the pictureswere judged more familiar than those in the Spanish one[t(253) = 4.32]. The reason seems quite obvious: Pic­tures were selected in the American context (things likea baseball bat, a football helmet, or a kettle are more fa­miliar to English speakers in America than to Spanishspeakers in Spain). With regard to complexity, the Span­ish sample judged the pictures as slightly more simplethan did the English-speaking one (t(253) = 6.60]. Per­haps the different size of the pictures reproduced by theslide projector or by the computer can account for the dif­ference. There is a larger significant difference when the Hvalue is considered [t(253) = 7.97]. The English-speakingsample had bigger H values than did the Spanish one. Be­cause H is an index of name agreement, it seems that thesample in our group showed less variability in the numberofnames applied to objects than did the English-speakingsample. Although the comparisons are rather global, thedifferences found are evidence that normative data forthis kind ofstimuli should be collected for different pop­ulations, because the responses that stimuli evoke in dif­ferent tasks can vary across cultures and/or languages.

Given this result, we performed a qualitative compari­son ofthose Spanish-English pairs whose difference wasexaggerated (we selected those scores 2 standard devia­tions above or below the mean). Following this criterionwe found 39 pairs for which the Spanish word surpassedthe English one in such a difference, but only 8 pairs forwhich the English word exceeded the Spanish one in sucha difference. The analysis of all these pairs helped us tofind some reasons for the discrepancy. One is that thereis a larger proportion of compound common words in

Table 1Summary Statistics for All Variables: Spanish and U.S.A. Samples

Picture-NameH* % Image Agreement Familiarity Complexity Agreement Variability

U.S.A. Spain U.S.A. Spain U.S.A. Spain U.S.A. Spain U.S.A. Spain (Spain) (Spain)

M 0.56 0.27t 86.59 82.30 3.69 3.71 3.29 3.12t 2.96 2.67t 4.06 2.61SD 0.53 0.41 14.34 21.68 0.58 0.60 0.96 1.11 0.89 0.93 0.49 0.59Median 0.42 0.12 3.72 3.84 3.32 3.06 2.93 2.52 4.11 2.6Mode 0 4.11 1.53 2.05 4.47 2.53Range 2.55 2.19 67 91.9 2.68 3.03 3.72 3.67 3.78 3.68 2.74 3.13Min 0 0 33 8 2.05 1.74 1.18 1.27 I 1.05 2.26 1.05Max 2.55 2.19 100 100 4.73 4.77 4.9 4.94 4.78 4.73 5 4.13QI 0.12 0.04 3.27 3.29 2.49 .2.16 2.28 1.98 3.74 2.16Q3 0.87 0.28 4.15 4.16 4.09 4.08 3.59 3.39 4.42 3.13Skew 1.5 2.39 -1.38 -1.42 0.96 -0.71 0.93 0.01 1.02 0.28 -0.57 -0.06Kurtosis 5.79 1.49 1.06 0.01 -1.32 -0.89 0.19 -0.49Validcases 260 254 260 254 260 245 260 254 260 254 245 245

*Increasing H values indicate decreasing name agreement. "Significanr t test differences at p < .0 I.

540 SANFELIU AND FERNANDEZ

English than in Spanish: In 14 ofthe 39 pairs, the Englishword was a compound (e.g., avian-airplane, sartim­frying pan, collar-necklace, pincel-paintbrush, bolsa­pocketbook,patin-roller skate, rnaleta-suitcase, regadera­watering can). Another reason is that the number ofalter­native names was always superior for the member withless agreement (8/8 for the pairs superior in English and31/39 for the pairs superior in Spanish). We also thoughtabout two other possible reasons: (I) the possibility thata higher H in one ofthe languages was due to the existenceofa very frequentsynonym (e.g., barril/tonel-barrel, cuenco/tazon-bowl, clavo/punta-nail, etc.) and (2) the use ofge­neric words instead ofspecific ones (e.g., shirt instead ofblouse, pan instead offrying pan, skate instead of rollerskate, glass instead of wineglass, etc.).

In conclusion, a detailed consultation of the ratingsobtained for each drawing with a particular sample is theoptimal strategy for selecting stimuli to be used withsubjects from that population.

Correlations Among the MeasuresThree correlational analyses were performed on the

data. The first one correlated the data provided by Snod­grass and Vanderwart (1980) with the data obtained inthe present study for H, image agreement, familiarity,and visual complexity. As shown in Table 2, there werefairly high and significant correlations for all the vari­ables. Correlations were higher for complexity and fa­miliarity than for name agreement (H and %) and imageagreement. This is probably because complexity and fa­miliarity werejudgments that were produced directly aboutthe picture or the object it represented, but not about theword used to name it. On the other hand, name agree­ment and image agreement were directly dependent onwords and the particular structure oflanguage. This pat­tern ofcorrelations is similar to that found for a Japanesesample (Matsukawa, 1983), for whom the lower correla­tions were also H values, percentage, and image agree­ment, demonstrating that naming pictures is not equallydirect in all languages (Table 2).

The second correlational analysis involved the dataobtained in the present study. Each measured variable

Table 2Significant Correlations Among the Measured Variables

in the Spanish and U.S.A. Samples(for Snodgrass and Vanderwart Pictures)

U.S.A. Sample*

Variable NA (H) % IA Fam Comp

Spanish sampleName agreement (H) .268Name agreement (%) .427Image agreement .557Familiarity .739Visual complexity .740

Japanese samplet .258 .185 .409 .858 .941

Note-v-Nx, name agreement; lA, image agreement; Fam, familiarity;Comp, visual complexity. All listed correlation coefficients for the cur­rent study and the Snodgrass and Vanderwart (1980) study are signifi­cant at p < .0 I. *Results from Snodgrass and Vanderwart (1980)."Results from Matsukawa (1983).

was correlated with the rest. Table 3 shows the signifi­cant correlations, which overall are not too different fromthe ones obtained by Snodgrass and Vanderwart (1980).Moreover, they are also similar to the ones obtained withchildren (Berman, Friedman, Hamberger, & Snodgrass,1989), Japanese (Matsukawa, 1983), and Dutch (vanSchagen, Tamsma, Bruggemann, Jackson, & Michon,1983) samples.

The third correlational analysis involved a compari­son between the variables measured in the present studyand the 11 variables for which the UVWP (Algarabel et aI.,1988) contains data. Table 4 shows the significant corre­lations obtained for the data from drawings that had theirmost frequently given name included in the word data­base. There is a high correlation (.52) between familiar­ity of the object depicted in the drawing and familiarityof the word. Also high were the correlations of imagevariability with two word variables: number ofattributes(.43) and meaningfulness (.46).

Factor AnalysisAccording to Snodgrass and Vanderwart (1980), the

interrelations among name agreement, familiarity, visualcomplexity, and image agreement were quite low, sug-

Table 3Significant Correlations Among the Measured Variables in a Spanish Sample,

for Snodgrass and Vanderwart (1980) Pictures, and Between Themand the Juilland and Chang-Rodriguez (1964) Frequencies

Variable NA (H) % IA Fam Comp Freq PicName 1-Var

Name agreement (H) 1.000Name agreement (%) - .740 1.000Image agreement .218 1.000Familiarity - .155 1.000Visual complexity -.136 -.4591.000Frequency .214 1.000Picture-name agreement .723 - .206 1.000Image variability - .276 .30 - .286 .327 - .349 1.000

Note-i-All listed correlation coefficients for the current study are significant at p < .01. NA, nameagreement; lA, image agreement; Fam, familiarity; Comp, visual complexity; Freq, frequency; Pic­Name, picture-name agreement; l-Var, image variability.

PICTURES STANDARDIZED FOR SPANISH 541

Table 4Significant Correlations Among Picture Variables and (UVWP)

Variables for the Concepts Available in the UVWP

scriptive ratings for a number ofpicture attributes of thedrawings previously presented by Snodgrass and Van­derwart (1980) with English-speaking subjects are nowavailable for Spanish-speaking subjects. With these data,pictures can be selected in a more accurate way becausetheir indices are specific for Spanish-speaking subjects.The different comparisons between the English and Span­ish ratings (and also Japanese; see Table 2) show that,despite the pictures being judged to be of similar com­plexity and familiarity, name agreement and image agree­ment are specific to the particular language.

Twoalternative explanations can be offered to explainthe differences found between our study and the originalone: The differences might be due to either language orcultural context. If differences in name agreement andimage agreement were due exclusively to cultural con­text, the familiarity correlations would not be so high;correlations of.74 in our sample and .86 in the Japanesesample suggest that the cultural contexts are comparableand very similar (i.e., objects that are familiar in one con­text are familiar in the other). However, even if this ar­gument were correct, the question remains open. Perhapsif another experiment were conducted with Spanish­speaking people living in the United States, the problemcould be solved. The finding ofhigh correlations betweensuch a sample and our sample for name agreement andimage agreement would indicate that the present differ­ences are due to language. Higher correlations betweensuch a sample and the Snodgrass and Vanderwart (1980)sample, by contrast, would indicate that the present dif­ferences were due to culture.

Inthe absence of relevant data, the question of lan­guage versus culture remains open and clearly in need offurther investigation. In the interim, attention should bepaid to the issue ofgeneralization of the results obtainedwith Spanish speakers from Spain to other groups ofSpan­ish speakers. Although Spanish speakers share a basiccorpus oflexical and grammatical knowledge, it might bethe case that different groups of Spanish speakers wouldshow different patterns ofresults because ofdialectal andcultural influences.

REFERENCES

.437

.462-.194

.251

Fam Comp PicName I-Var

.262

.173 -.128 .269

.214 .183-.214

Picture Norms

IANA(H)Word Norms

Letter meanings"Letter frequency]Letters"ImageryMeaningfulnessAttribute - .231Concreteness .217Categorizability .229 .218 .193Familiarity - .206 .526 - .259 .192Pleasantness .180 .269Syllables· - .158

Note-All listed correlation coefficients for the current results are sig­nificant atp < .05. All valid cases equal 85, except in • (211 valid cases)and t (89 valid cases). NA, name agreement; lA, image agreement;Fam, familiarity; Comp, visual complexity; PicName, picture-nameagreement; I-var, image variability.

gesting that the four measures represented largely inde­pendent attributes of the pictures. They also assumed thatpicture-name agreement and image variability were twovariations ofthe image agreement task, and so the ratingsin those two tasks related to the same attribute ofpictures.To examine these assumptions and to obtain further dataon the structure of attributes, we conducted a principalcomponents factor analysis and a varimax rotation.

The analysis showed that only four factors explainedaltogether 88% of the variance. Table 5 shows that Fac­tor 1 loads on image agreement and picture-name agree­ment. This fact is congruent with the assumption thatboth variables refer to the same underlying attribute ofpictures. However, Factor 2 loads positively on complex­ity and negatively on familiarity, implying that visuallycomplex pictures tend to be unfamiliar, or, in other words,familiar objects are usually simple. Factor 3 shows thatimage variability is independent of image agreement. Itseems that variability of images is closer to the richnessof the concept (familiarity might be implied) than to thevividness of the image the concept activates. Finally,Factor 4 loads on name agreement, a result that reflectsthe independence of this attribute.

CONCLUSION

The main goal of the present research was to collectnormative data for pictorial stimuli that could be used inresearch with Spanish-speaking samples. As a result, de-

TableSFactor Analysis (Varimax Rotation)

Variable I 2 3 4

Name agreement (H) - .083 .035 - .152 .981Image agreement .915 -.061 -.135 -.094Familiarity -.128 -.757 .419 .001Visual complexity -.065 .915 .121 .044Picture-name agreement .919 .089 -.138 -.010Image variability -.214 -.066 .917 -.175

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SNODGRASS, J. G., SMITH, B., FEENAN, K., & CORWIN, J. (1987). Frag­menting pictures on the Apple Macintosh computer for experimentaland clinical applications. Behavior Research Methods, Instruments,& Computers, 19,270-274.

SNODGRASS, J. G., & SURPRENANT, A. (1989). Effect of retention inter­val on implicit and explicit memory for pictures. Bulletin ofthe Psy­chonomic Society, 27, 395-398.

SNODGRASS, J. G., & VANDERWART, M. (1980). A standardized set of260 pictures: Norms for name agreement, image agreement, famil­iarity, and visual complexity. Journal ofExperimental Psychology:Human Learning & Memory, 6, 174-215.

VANDERWART, M. (1984). Priming by pictures in lexical decision. Jour­nal of VerbalLearning & VerbalBehavior, 23, 67-83.

VAN SCHAGEN, 1.,TAMSMA, N., BRUGGEMANN, E, JACKSON, L. L., & MI­CHON, J. A. (1983). Namen en normen voor plaatjes. Nederlands Ti­jdschrift voor de Psychologie, 38, 236-241.

WILSON, M. (1988). MRC psycholinguistic database: Machine-usabledictionary, version 2.00. Behavior Research Methods, Instruments,& Computers, 20, 6-10.

NOTE

I. 'The H value captures more information about the distribution ofnames across subjects than does the percentage agreement measure. Forexample, if two concepts both are given their dominant name by 60%of the subjects, but one is given a single other name and the second isgiven four other names, both concepts will have equal percentage agree­ment scores, but the first will have a lower H value" (Snodgrass & Van­derwart, 1980, p. 184).

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