Memory & Cognition1983, Vol.11(1), 83-92

Associativeasymmetry, availability,and retrieval

DAVID C. RUBINDuke University, Durham, North Carolina 27706

Associative frequency, the ease with which a word comes to mind in free association, istaken as a measure of general response availability. As expected from this view, in bothcontrolled experiments and in reanalyses of previously published correlational data, highassociative frequency words were judged to be more familiar and were easier to recall butharder to recognize than low associative frequency words, even with meaningfulnees, imagery,length in letters, and frequency excluded as factors. When used as follll in a recognitionexperiment, high associative frequency words attracted more responaes than low aaeocietivefrequency words. In addition, associative frequency and meaningfulness correlated onlymoderately and had different patterns of correlations with other variables, suggesting thatthe number of associationsleading to and from a word differ.

Words that come to mind easily, that is, words thatare available, are generally thought to be easier to recall.Although this idea has been tested for many specific sub­domains or categories of words (e.g., Asch & Ebenholtz,1962; Dale, 1967; Deese, 1965; Leieht, 1968; Tversky &Kahneman, 1973), with the exception of frequency ofoccurrence, no general measure of availability has beenformulated. One main hindrance to such a formulationfrom an associative or network framework may be thefailure to apply the evidence that associations amongwords are often asymmetrical (Anisfeld & Knapp, 1968;Deese, 1965; Ekstrand, 1966; Paivio, 1971; Thorndike,1932; cf. Asch & Ebenholtz, 1962, and Horowitz,Norman & Day, 1966). If associations are not alwayssymmetrieal, then meaningfulness, a measure of thenumber of associations emanating from a ward, is notthe general indieator of associative strength that it isheld to be, An additional measure, the number ofassociations leading to a word, is also needed. Moreover,the number of associations leading to a word should be agood index of how often a word would be evoked over asampIe of stimuli and, thus, should be a good index ofresponse availability.'

Associative frequency is the number of times a wordis given as a first associate to a sampIe of stimulus words,here the 200 stimulus words of Palermo and Jenkins(1964). Thus, associative frequency can be thought ofas a general measure of availability for isolated wards.That is, although certain words are more likely to come

Support for this research came from a Duke UniversityResearch Council Award. The author is indebted to Reed Hunt,Gregory Kimble, and Gregory Lockhead for their comments onan earlier version of the manuscript, and to Allan Paivio for rnak­ing his familiarity ratings available. Reprints are available fromthe author, Psychology Department, Duke University, Durham,North Carolina 27706.

83

to mind in the context of a category name (Dale, 1967),a list of other words (Deese, 1965), or an associatedword (Tversky & Kahneman, 1973), high associativefrequency wards are more likely to come to mind ingeneral. In Underwood's (1965) terms, associative fre­quency is a measure of average frequency of a word asan implicit associative response. In a directed graph(Kiss, 1968, 1975), associative frequency is indegreevalue.

If the assumption that associations are asymmetriealand the assumption that associative frequency is a goodmeasure of availability are correct, what predictions canbe made? From the first assumption, it should followthat associative frequency and meaningfulness shouldnot be the same variable. From the second assumption,it should follow that high associative frequency wordsshould be easier to retrieve in free recall, harder to recog­nize, more effective as foils, and more familiar in judg­ment tasks. The prediction about recall follows fromalmost any model of retrieval. The predictions aboutrecognition follow directly from Glanzer and Bowles(1976), as well as from Mandler (1980) and otheraccounts of recognition that have dealt with a similarproblem, the word-frequency effect. The predictionabout familiarity follows directly from Tversky andKahneman (1973).

In order to examine some of the predictions made,one of the few studies that has investigated associativefrequency, the one that led to this investigation, will beexamined. As part of a large correlational study using125 words (Rubin, 1980), 34 independent variableswere used to prediet which words would be remern­bered in various tasks. The independent variablesincluded length in letters, orders of approximationto English, using letters and phonemes, orthographiedistinctiveness, pronunciability, imagery, concreteness,rneaningfulness, categorizability, age of aequisition,

Copyright 1983 Psyehonomie Soeiety, Ine.

84 RUBIN

frequency counts, goodness, emotionality, associativefrequency, and assorted others. Dependent variablesincluded paired associate learning and free recall with18 words/list and a 5-sec presen tation, free recall withall 125 words shown in one long list for 1 sec each,surprise free recall following a lexical decision task,and surprise free recall following a paired associatetask.

From this study, it is possible to provide an initialevaluation of both the claim that associative frequencyshould be an effective predictor of free recall and theclaim that it should function differently from meaning­fulness. The correlation of associative frequency andmeaningfulness, calculated over the 125 words used inthe study, is .42. This should be considerably lowerthan the reliabilities of the two variables in this sampIeof words, as both variables correlate more highly withother variables in the study. Examinations of howthe two variables function in memory tasks, however,are more revealing.

Meaningfulness is the ease with which a word bringsother words to mind. Lists of high meaningfulness wordsshould, therefore, be easy to learn, because each wordin the list might lead to the recall of many others. How­ever, the prob ability of any given word being recalledshould depend on how easily it comes to mind, not onhow easily it brings other words to mind. That is,associative frequency should be a better predictor ofrecall than meaningfulness. Rubin (1980) bears this out.On the seven independent free-recall tasks used, associa­tive frequency correlated more highly with the percent­age of subjects recalling each of 125 words than didmeaningfulness, with average correlations with the recalltasks of .40 and .23, respectively. In fact, associativefrequency was the best single predictor, of 34 predictors,for most of the free-recall tasks. (In this and all othercorrelations reported, the logarithms of associativefrequency and of frequency are used.)

The added control of paired associate learning allowsa more direct test. If meaningfulness is a measure of howeasily a word brings other words to mind, and if associa­tive frequency is a measure of how easily other wordsbring the word in question to mind, then one wouldexpect high meaningfulness words to be good stimuluswords in paired associate learning, and high associativefrequency words to be good response words. In Rubin(1980),125 words plus a dummy word were made into63 pairs. The first subject saw these pairs in a pairedassociate task, and the next subject saw the same pairswith the stimulus and response members interchanged.Various randorn pairings and orders were used. Thenumber of times each pair of words was recalled wastabulated separately for both the stimulus and theresponse word. In this way, subjects and either theresponse or the stimulus words were averaged over, leav­ing only the stimulus or the response words determiningthe recall score. Meaningfulness correlated .47 with the

scores tabulated by stimulus words, but only .21 withthe same scores tabulated by response words. On theother hand, associative frequency correlated only .27with the scores tabulated over stimulus words, but .58with the scores tabulated by response words.

Although associative frequency is not the same asmeaningfulness, it still could be the same as frequency.Frequency is a measure of how easily words come tomind in running text (Skinner, 1936), whereas associa­tive frequency is a measure of how easily words come tomind in isolation (Ervin, 1963). In fact, Howes (1957)attempted to demonstrate that frequency in normalusage and frequency in association experiments areempirically the same. Howes showed statistically that ifthe complete range of word frequency and associativefrequency, not just the relatively few common wordsthat occur more than once per million or more, couldbe measured and used, the correlation would be .94 andprobably higher. Nonetheless, over the limited range ofwords with a frequency of approximately 1 per millionand greater and an associative frequency ofapproximately 1 per 600,000 and greater, the correla­tion is lower: .55-.80 for the five frequency counts usedby Rubin (1980). As the words mentioned in a sampIeof one million words are typical of the words that makeup most of English usage (Rubin, 1974) and most psy­chology experiments, the lower correlations provide afairer index of the agreement of associative frequencyand frequency in actual use. More important, the twovariables behave differently in the Rubin (1980) studyand elsewhere. Of special note is the observation thatfrequency is not a good predictor of free recall in studiesusing lists of mixed, as opposed to uniform, frequency(Christian, Bickley, Tarka, & Clayton, 1978; Peters,1936; Rubin, 1980; Rubin & Corbett, 1982), whereasassociative frequency is often the best predictor offree recall for mixed frequency lists (Rubin, 1980).That is, in mixed frequency lists, usually only a weaklinear relation is found between frequency and recall,with rare words often showing greater recall than com­mon words (e.g., Duncan, 1974; Gregg, 1976; Peters,1936; Rubin & Corbett, 1982), areversal of the find­ing with uniform frequency lists and in a direction oppo­site to that found with associative frequency. Neverthe­less, frequency and associative frequency do correlatefairly highly, and care must be taken to separate the twovariables.

Thus, in one sampIe of 125 words using many mem­ory tasks and independent variables, associative fre­quency emerges as one of our best predictors of freerecall. Although theoretically related to and empiricallycorre1ated with meaningfu1ness and frequency, it doesappear to be a separate variable. Neverthe1ess, one sam­pIe is not enough. The value of associative frequency inpredicting free recall will be assessed in a correlationalstudy with a new, larger sampie of words, and then ina more controlled experiment. The claim that associative

frequency is a good measure of availability will then befurther examined using a recognition study and familiar­ity judgments.

EXPERIMENT 1: A REGRESSION ANALYSIS

The usefulness of associative frequency relative toother more standard variables and associative frequency'srelation to those variables can best be assessed in a corre­lational study. Such a study should use a large numberof words that cover a good range of values of the vari­ables to be compared. Recall values are currently avail­able for only one such set of words. Christian et al.(1978) had subjects recalllists of words using a standardlist-learning paradigm in order to obtain percentagerecalled values for 899 of Paivio, Yuille, and Madigan's(1968) 925 nouns. A total of 32 subjects saw each word.The resulting percentage of recalled values had a reli­ability of .57.

Two cautions must be exercised, however, in usingthe Christian et al. (1978) values. First, 121 of the 899nouns overlap with the Rubin (1980) study, making thetotal set not completely independent of the studyoriginally arguing for the value of associative frequency.Second, for the 121 words that overlapped with theRubin (1980) study, the Christian et al. measure was notthe most representative recall task, having the highestcorrelations by a notable amount with both imagery andassociative frequency. On the positive side becauseChristian et al. used Paivio et al.'s (1968) words valuesof imagery, meaningfu1ness, and other variables are avail­ab1e.

Including many variables in a multiple regressionanalysis can lead to technical problems, especially ifsome of the variables are highly correlated (Rubin,1980). For this reason, a small subset of possible predic­tors .of free recall was chosen for the regression analysis.Rubin (1980) found that six factors underlie most of theexperimental tasks and variables that psychologists use.These factors, if labeled by their highest loading vari­ables, would be length in letters, concreteness, logK~~era and Francis (1967) frequency, recal1, emotion­ality, and goodness. Associative frequency did notappear as aseparate factor but loaded .44, .35, .61, .25,.13, and .05, respectively, on the six factors listed.Values for the variables that label the first three factorsa.re availab~e and could be included in a multiple regres­sion analysis along with associative frequency. Values forgoodness and emotionality are not available and recallis the dependent variable in question. Because imageryappears to be a better predictor of recall than concrete­ness (Christian et al., 1978; Frincke, 1968; Paivio, 1968;Rubin, 1980), imagery will replace concreteness in theanalyses, In addition, meaningfulness will be includedbecause of its theoretical relation to associative fre­quency.

AVAllABILITY AND RETRIEVAL 85

Results and DiscussionAssociative frequency values were calculated for

Paivio et al.'s (1968) 925 nouns, using Palermo andJenkins' (1964) word association norms. FollowingRubin (1980), responses listed in the index of Palermoand J enkins, bu t not in the actual tables, were assumedto have a frequency of 2. The 460 nouns with valuesgreater than 0 are given in Table 1. Correlations for the925 nouns among available variables are listed in Table i.Because many of the words have associative frequencyvalues of 0, the correlations with log associative fre­quency were done both with these 0 values set to .5before the logs were taken and with the 0 valuesomitted.

Multiple regressions were performed for all 899words, for the 450 of the 899 words that had associativefrequencies greater than 0, and for the 346 of the 899words that had associative frequencies greater than 0and that were not inc1uded in Rubin's (1980) study.The last set of words was used to exclude the sample onwhich associative frequency and recall were first foundto be related. The standardized regression weights(betas) and the increases in R2 when each variable isentered into the regression equation last are given for thethree analyses in Table 3. The three analyses, fortunately,provided similar conc1usions, although the effects ofassociative frequency were reduced somewhat when itsrange was reduced by eliminating its 0 values. Imagery~a~ the best predictor, with associative frequency pro­viding a good deal of independent predictive power~ncreasing the variance accoun ted for by imagery, mean­ingfulness, frequency, and length combined by between12% and 20% in the three analyses. The multiple regres­sion coefficients themselves are impressive, consideringthat the recal1 variable had a reliability of only .57.

Rubin's (1980) finding that associative frequency isa good predictor of recall, both by itself and when usedwith other standard variables, is supported by Experi­ment 1. The regression analysis allows comparisons to bemade among many variables but suffers from two main!imitations. First, the recal1 measure used may not havebeen representative of other recall measures (Rubin,1980). Second, the units of analysis were words, notpeople , so the units were not independent, and inferen­tial. statis~ics could not be applied. Although the samebaSIC finding was obtained for two samples of words anda total of seven independent free recall measures asi~ple infe~ential test that varies associative freque~cywhile holding as many other variables constant aspossible is still lacking.

EXPERIMENT 2:A CONTROLLED EXPERIMENT

The main decision in designing the controlled experi­ment was to decide which of the multitude of variables

86 RUBIN

Table 1Nonzero Associative Frequency Values for Paivio et a1.'s (1968) Norms

ABILITY 4 COlLEGE 2 GLACIER 6 MATERU\ Tl Raa 26.eOOE 4 COMPUlSON GLORY 8 MATHEM. ICS U SlDNESS 122Aey~~ 4 CONFIDENCE 8 ä8~TON lU ME4DOW

~~nr50

t~G ä ION 1~ ~8~~UCT 4=~NING 7r~ 22248 ALA YAGONY 6 CORE 13 Glt4NDMOTHEIt 25 MfMOItY 16 S4LUTlTION 44IR

i~l ~ORN84 1:4UTY 1563 M NACE 6 S"WTE 10

U~OHOL 8R~~~ 13~

BU~~COPE t~ U RtET 1~AL EBU 20 R~ :"lltG"TOR 4 OST 28 GREEN 1~99 4 SCIENCE 43t=8~~.NCE 9 rTTA GE p3 GRIEF ~3 MINO 612 SEA 1631

ß~e& u H"~L t3 =n~~~EF 58 ~U~ON 3U"NGlE 30 HA HER 21t~rnL 2n~

R "T R 6 HAPPINESS 603 MISSILE 6 SERIES 4ERiATURE 25 HARDSHIP 29 MOMENT 31 rAD~W InA~~l~ 28$ tin ~OM tf HA~P ~8 M8N~RCH 12n HAM

:Nx1 ~Y HA R~D M N Y HIP23 AWN 6 HEll H 1156 MONK 10 SHOCK 22

APPEARANCE 32 gU\~GHT 30\tHElR ING 4 M~TH 1t i~~iK 2Ut~~LE ngg ~iA~EN nDEED 6HIgTORY =os8UITO

AR"'Y lOH DELL 4 54 MgSS HAg SICKNESS 6664RRON OEMOCRACY 26 HOHE 3106 M THER SILENCE 148UMHICS

4B~~O+ION 2l HONOUR

6~A MOU~T4IN 4U ~INGER 18It HQPE MULE KIN 115llMQSPHERE DUMOND 21 HORSE 406 MURDER 38 SKULL 20

AUTHOR~g DIRECTION 15 ~8nllth "35 NUl 1955 SKY 1565

t~~2~~BILE DIRT 597 2~ ~~~R~~ITY ~ ~H~~ER U49~ BJitnaNE9 HOTEbBABY 246 6 HOUN 6 NEWSPAPER 10 SNAKE 60

BACTr U2~ 8~~SI~RY p~

HOUR 58 NONSENSE~~

SOll 137B4ND T~~~ÖR 4422 NUN ~~NATA !~BANN R 6 1~9 NURSERY 6 EUER8AR 53 DOll HURDLE 13 OATS 4 SPEECH 83

RU~~~NT 1~gOLLAR 8 IOEl 47

8eeil~~~E " SPIN4fH 10D~~ l1t~ ILLUSION 4 4 SP RI 48HST 84 INFANT 140 °böAN 592 SPRAY 8BEGGAR 8 DR4"'A 4 INJURY 10 o R 14 S~UARE 151BELONGINGS 6 BR~AM 877 INK !6 rfliSR 127 S UN 21

lnSU GE381'

R AMER 4l~iECT 144~ ~I~M N 8

n5~M lOHDRESS 508 4BLASPHEMY 4 DUHHY 4 IN UNCE " ORIGIN 1 rNE

121BlMTER 4 DUST 20 INiTRUM~NT 92 OVEN 448 T RM 14BL 0 286 ~~nH 26 IN ~RKS 10 8=~USHIP U iitnERRY "BLOOM 98 228 NT P4 TE " 362BlOSSOM 4 EFFORT 10 IRON 135 PUNTER 4 TRENGTH 6CJB8ARD dU ~~iow ~ IIEM 1i8 PAlf~E 3" STRING 11tJ Il 468 STUaR08~ L PHANT 15 JELLY 40 U~y 61 STUDENT 27BORE DOM 6 ENGINE 38 JOKE 8 PASSION 6 STYLE "BOH 51 ~RRAN2 4 ~83GE 418 PEACH

1~~ ~~8~R 91~22A UHI ATION 4 PENC n,BBULb~R eXCUSE 156 ~USTI~E 21 PEP 6 SUNSET 17BOWl 53 EXHAUSTION 8 EROS NE 4 PEPPER 2095 SNAMP 6BOX 1023 iXPk-NAPON H ~~~6b~ss Ji P~RM t 5SION 4 lAB~E 243!BR IN 5U :GRHS ON ~ ~~8N 3JU T~~ r~R 26BRE ST 4 U~~ 8BREElE zn fACT 38 B2 PfCTURE 136 THIEF 20But~gING FACT~RY ~2 KNOWlEDGE 24 PIPE 6n THOUGHT 410BUl T 7~ FA~T SY l4D 20H P~'AIN TICKET 83tBUTCHER HE 4 4KE P ANK 4 T MEBUTTEP. 19H FAULT 10 LANDSCAPE 4 PLANT 946 TOAST 98BUTTERFLY FELINE

73~LARK 4 ~bHiVRE 82 l88tCCo

2:iHa~N 3~i FIRE ~4W lOUfIR~PLACE 6 AWN POLE :, tOWERCANDY 893 HA 95 L~~DeR 120 POLICEMAN OY Z14

CANE 12 HM~ li t ~~RE 4 POStTbON H TREE 620CAR 1776 l~MON4DE 54a P8"1 TRO~BLE HgCASH 6 FlOWER Z005 P WE 65 {RU KCAt 3597 FOAH 10 LINGTH 78 PRURIE 6 RUMPEl 30r ~RPILLAR $8 FORI~'4D 4t

L OPARD 10PRr~R lU

TRUTH 178AT LE 4 LpTER 292 ~R S NT U"'~RElLA 6Ell 11 f8R 63 L BRARY 69 R OE VA UUM 12

CELlAR 8 FORM 14 LIFE «;06 PRIEST 137 VALLEY 196rAIR 3857 fORTUNE 19 tI=~ U PRISON 24 VEGEIABLE 1082HAN~E 12 FO~ n INK PRMoN,R 10 ~1~~u~E 53HAR 6 FR EOOM 4 24 "CHIEF 56 FRIEND 397 LIP 6 ~=OF~§SOR 0\ VISION 89CHILD 2231 FROG

I~ULOCKER B PROPERTY 6 VO~C"NO 4

~HIN 4 FUN ~Be~ 8U ~M~~lNG U =~ ~IH 8HZHRISTMAS 156 FURCHURCH 286CJ Fl)RNITURE 112 lOYALTY 4 8UANTITY 4 WEAPON 32pGAR 23<) GUETV 4 LUMP 15 UEEN 2Slt6 WELFflRE 26IRCLE 601 ~~~~~N 121 =t~~~~ ~g UlU2~YON II WHALE 8CITY 399 WHEll 76Cl All 21 GEM 4 MAGAZ INE 8 REfRIGERATOR 47 WIFE 93ELO~K J! GENDER 6 MAKER 41 REPTILE 4 "IN~OW 473b~ ytNG 8~=l~iMAN * Qt~~~~ It ftESUURANT 4

=l~ ER !9~nUAl 4CODE 4 GHOST 83 MARKET 18 RIVER 550 WOMAN 2200COFFEE 49 GIFT 80 M4RH AGE

:~ ROBBER 134 WOOD~ B"COIN 14 GIRL 5552 ..4S R ROCK 570 WORL 415

AVAllABILITY AND RETRIEVAL 87

Table 2Correlation Coefficients Among Variables

3 4 5 6 7 8 9 10 11 12

1. Log Associative Frequency -.50 .50 .51 .43 .29 .46 .63 .57 .66 .382. Log Associative Frequency: No Zeros -.33 .33 .35 .31 .24 .32 .56 .46 .53 .403. Length in Letters -.97 -.92 -.35 -.30 -.33 -.27 -.27 -.41 -.274. First-Order Approximation .93 .32 .28 .32 .28 .30 .43 .255. Second-Order Approximation .28 .24 .29 .31 .34 .46 .236.Imagery .83 .72 .34 .09 .33 .447. Concreteness .56 .10 -.06 .16 .408. Meaningfu1ness .48 .28 .43 .319. Familiarity .76 .76 .13

10. Log Kuöera-Francis Frequency .77 .0911. Log Thorndike-Lorge Frequency .1712. Free Recall

Note-Uorrelations are based on 925 words, except [or free recall, which is based on 899 words, and log associative frequency withno zero values included, which is based on 460 words. First- and second-order approximations to English are information theorymeasures of the probability ofgenerating the word by chance on a lettcr-by-letter basis (values from Rubin, 1981). Variable 6, 7, and8 are from Paivio et al. (1968); Variable 9 is judged printed familiarity from Paivio (Note 1). For Variables 10 and 11, zero fre­quencies were replaced by .5 and A and AA words were replaced by 50 and 100. respectively.

Table 3Multiple Regressions on Percentage Recalled

Overall(R = .505, N = 899)

Sampie-----

Af > 0(R = .553, N = 450)

AF > 0 No Overlap(R = .526, N = 346)

Variable Beta Weight R2 Increase Beta Weight

Imagery .356 .053 .378Log Associative Frequency .299 .042 .239Log Kuöera-Francis Frequency -.108 .007 -.125Meaningfu1ness -.067 .002 -.008Length --.049 .002 .009

R2 lncrease

.073

.034

.000

.000

.014

Beta Weight

.356

.201-.018

.030-.145

R2 Increase

.068

.029

.000

.000

.019

Note-R = multiple-regression coefficient; N = number of words in sampie. The R 2 increase is the increase when the variable isentered into the multiple-regression equation after the foul' other independent variables.

that are related to recall to contra!. An attempt wasmade to contral the same variables that were included inthe multiple regression analysis in Experiment 1 for thesame reasons that they were included there.

MethodSubjects. As part of a course requirement, 70 undergraduates

participated in the experiment.Materials. A sample of 64 high and 64 low associative fre­

quency words were desired for the list-1earning experiment. Inorder to obtain these words, the 465 words with an associativefrequency of 0 and the 191 words with an associative frequencyequa1 to or greater than 50 were initially se1ected. To try toequate the groups in 1ength in letters, imagery , meaningfulness,and frequency, the 40 longest words, the 40 words lowest inimagery va1ue, the 40 words lowest in meaningfulness, and the40 words of lowest frequency were removed from the lowassociative frequency group, and the 12 shortest words, the 12words highest in imagery, the 12 words highest in meaningful­ness, and the 12 words of greatest frequency were rernoved fromthe high associative frequency group. This procedure wasrepeated several tim es until the mean values for imagery andmeaningfu1ness balanced in the high and low associative Ire­quency groups. By choosing words that were of proper length,as weil as of proper frequency , on the last frequency itcsation,it was possible to also balance length in letters. Freq ucncy cou ldnot be balanccd , but the difference between the mean values of

the two groups was made relatively small. The difference inthe mean values of frequency , however, is not seen as a seriousflaw, because the effect of frequency in separate lists of high andlow frequency words is small when compared with the differencein mean value of frequency used here (Deese, 1969; Hall, 1954).Table 4 presents the statistics for the dependent variables con­trolled in the final sampie of 64 high and 64 10w associativefrequency words. Values for associative frequency and for thefree-recall measure that was not used in the se1ection of thewords are also included in Tab1e 4. T tests calcu1ated overthe 128 words in the two sampies are provided as a descrip­tive statistic comparing differences between the group meansto differences within the groups. If the t value for free recallwere squared, it could be considered as an F 2 value (Christianet al., 1978; C1ark, 1973) for an ANOVA run using Christianet al.'s data. lt may be noted that the slight difference betweenthe groups on length, imagery, and meaningfulness are all in thedirection that would work against the associative frequencyhypo thesis.

Proeedure. Four lists of 16 high associative frequency wordsand four lists of 16 low associative frequency words were alter­natcd, uniform lists being used in an attempt to further general­ize the results of Rubin (1980) and Experiment 1, which usedmixed lists. A second order of presentation was obtained byreversing hoth thc order of the eight lists and the 16 wordswithin each list. Approximately half of the subjects saw eachorder. Words were presen ted for 3 sec each using a slide projcc­tor. A slidc of a thrce-digir number cnded each list. The subjects

88 RUBIN

Table 4Statisties for the High and Low Associative Frequency Groups

High Group Low Group

Variable Mean SO Range Mean SO Range t Test

Length 5.92 1.52 4.00-10.00 5.83 1.02 4.00-7.00 .41Imagery 5.55 .93 2.7Hi.53 5.57 .69 4.43-6.77 .15Meaningfulness 6.22 .73 4.04-7.36 6.26 .66 5.32-8.19 .33Kucera-Francis Frequency 27.26 2.65 2.00-105.00 9.87 2.87 2.00-135.00 5.65Associative Frequency 189.14 2.86 50.00-2292.00 .00 .00 .00-.00 39.95*Free Recall .46 .13 .19-.78 .36 .12 .06-.84 4.24

Note- The t tests are all based on 128 words, exeept the free reeall measure, whieh is based on 126 words. As the words are notindependent, the t tests must be eonsidered descriptive. All ealeulations [or Kucera-Francis frequency and associative [requency arebased on log frequency, The means are, therefore, geometrie means, and the standard deviations are conversions from the actuallogarithmie ones. "Single-sample t test against a value of O.

recorded subtractions by 3 from this number for 30sec, atwhich time they were asked to write their recalls. Verbatimrecall was encouraged, but the subjects were encouraged toguess. Thirty seconds after the subjects, who were run in groups,cornpleted the 90-sec recall period of one list, the next list waspresented. A practice list of words, drawn from Paivio et al.(1968), preceded the eight Iists analyzed herc. Due to a problemwith one slide, one high and one matehing low associative fre­quency word were rernoved from the analysis.

ResuItsThe high associative frequency words were recalled

61.5% of the time, as compared to 53.8% of the time forthe low associative frequency words [t(69) =7.42,p< .001]. Considering the first two experimentstogether, associative frequency appears to have a reliableand substantial effect on the level of recall, both inmixed and uniform lists, even when the other majorvariables affecting recall are constant. Although onecould argue that the actual size of the difference in recalllevels obtained in this experiment is not large, any differ­ence found after imagery, meaningfulness, and length inletters are controlled is impressive, especially becausesuch controls are not usually applied in psychology. Infact, given the corre1ation of associative frequency withthese other variables in uncontrolled sampIes of words,it may be that associative frequency was responsiblefor part of their effectiveness.

EXPERIMENT 3:A RECOGNITION EXPERIMENT

The recognition paradigm offers a good test of theavailability interpretation of associative frequency.Assuming that the explanation of recognition offered byMandler (1980) is correct, two processes are used todetermine whether a given word appeared on arecentlist. One process is a judgment based on familiarity, andthe other is a judgment based on success in retrievingwords. If high associative frequency words are also highavailability words, the familiarity of the word should notbe greatly affected by one recent presentation. That is,

it should be difficult to distinguish the level of familiar­ity of a recently presented high associative frequencyword and the level of familiarity of the same word if itwere not presented. Similarly, it should be easy todistinguish the level of familiarity of a recently pre­sented low associative frequency word and the sameword if it were not presented. For example, consideryour confidence in judging whether the words "water"and "wigwam" were presented to you in the last hour,both for the case in which the words were targets andfor the case in which the words were foils.

The familiarity judgment favors low associative fre­quency words. The retrieval judgment, as shown in therecall experiments, might seem to favor the high associa­tive frequency words, because these words are easier toretrieve. Again, however, the comparison to a baselinewould reverse the direction of the effect. That is, per­ceived difference in ease of retrieval between words thatwere and were not on the original list should be greaterfor low associative frequency words, as one recentpresentation should have more of an effect on their easeof retrieval.

Thus, given the availability interpretation of associa­tive frequency and a model of recognition based onfamiliarity and ease of retrieval judgments, low associa­tive frequency should be recognized better than high.This reversal is the same as is often noted with word fre­quency (Glanzer & Bowles, 1976; Mandler, 1980) andcould be derived from other models of recognition thatcan handle the word frequency effect. In fact, theGlanzer and Bowles model explicitly makes use ofassociative frequency (although it is never measured) toexplain the word frequency effect in recognition, as domodels of false recognition based on implicit associativeresponses (Anisfeld & Knapp, 1968; Underwood, 1965).

MethodSubjects. Seventy-five undergraduates drawn from the same

population as that of Experiment 2 participated.Procedure. The128words from Experiment 2 were presented

to approximately halfof the subjects in one long list,alternating

high and low associative frequency words. The reverse order ofthis list was presented to the remaining subjects. A Lö-sec pre­sentation rate and the same physical environment as Experi­ment 2 were used. The 30-sec retention interval was filled withsubtraction by 3s from a three-digit number. Subjects chose thecorrect word from among the four alternatives printed on eachline of a I 28-line form. The subjects were inforrned of the natureof the task before the words were presented and were instructedto guess if necessary, but to circle one and only one word oneach line.

Two sets of forms were used. The foils were identical andidentically placed, three foils to a line on both forms. The foilswere drawn randomly from the Paivio et al. (1968) wordsremaining after the targets were selected, with the restrictionthat theirvalues of associative frequency, length, imagery, mean­ingfulness, and frequency all fall within the range of values ofthe target words. For one order, the 128 target words wereassigned randomly to the 128 lines of foils. For the otherorder,a second random assignment was made with the restriction thateach line that had a high associative frequency word in the firstorder would now have a low associative frequency word, andvice versa.

ResultsSubjects correctly recognized 60.8% of the high

associative frequency words and 66.6% of the low associ­ative frequency words [t(74) = 6.06, n< .001], aresult of approximately the same magnitude as, butin an opposite direction from, the results of Experi­ment 2.

Experiment 3 was not designed to investigate the roleof the foils: They were identica11y placed for a11 subjects,confounding their positions with their other properties.Nevertheless, the view of recognition put forth here doesmake a testable prediction about the foils. Althoughlow associative frequency words should be recognizedmore often than high associative frequency words, highassociative frequency folls should attract more falsealarms than low associative frequency words (Anisfeld &Knapp, 1968; Glanzer & Bowles, 1976; Underwood,1965). This is because unless low associative frequencywords have appeared recently, they should not seem atall familiar. Using log associative frequency in all calcula­tions, there was a sma11 but statistically significant effectin this direction. The geometrie mean associative fre­quency of the foils was 4.6, whereas the geometrie meanassociative frequency of the foils circled by each subjectwas 5.7 [t(74) =4.20, P< .001] .

EXPERIMENT 4: ASSOCIATNE FREQUENCYAND FAMILIARITY

The effects of word frequency on recall and recogni­tion have been claimed to be at least partia11y due to theeffects of associative frequency. Of special interest is theclaim that people will judge whether they have seen aword among a set of recently presented words by com­parison to a baseline that depends, in part, on associativefrequency, rather than just on frequency of occurrence.If these claims are true, then it might be expected thatpeople's conscious judgments of the familiarity ofwords would also depend, in part, on associative fre-

AVAllABILITY AND RETRIEVAL 89

quency (Leicht, 1968; Tversky & Kahneman, 1973).That is, if people judge the probability of past occur­rence in a recognition experiment against associativefrequency, then they might judge the probability of pastoccurrence in general using associative frequency.Moreover, if associative frequency is really a measure ofavailability, then the work of Tversky and Kahnemanwould suggest not only that associative frequency shouldaffect reca11 asdemonstrated, but also that it should affectfamiliarity. In particular, if words with high associativefrequency are more available, then they should bejudged as occurring more frequently than they actuallydo.

Judgments of familiarity agree quite weil withobserved word frequency (Carroll, 1971; Shapiro, 1969),well enough that some have considered replacing objec­tive counts of frequency with judgment scales (Carroll,1971; Frumkina & Vasilevic, 1974). Nevertheless,systematic differences between the two measures arepossible (Rubin, 1976). For instance, Galbraith andUnderwood (I973) found that abstract words havegreater perceived frequency than concrete words of thesame objective frequency, and Tversky and Kahneman(1973) found in a host of tasks that more availablewords and events were judged to be more frequent.

As a test of the notion that judgments of familiarityare due in part to associative frequency, judgments offamiliarity compiled by Paivio (Note 1) will be predictedusing measure of frequency of occurrence and associa­tive frequency. To Insure that associative frequency isnot just one of many variables that have minor, butnoticeable, roles in the judgment of familiarity, thevariables of concreteness, as used by Galbraith andUnderwood (I973), and of length in letters will beincluded. The latter variable correlates with familiarityand would be easy to use in judging it. In addition, takentogether, length in letters, frequency, and concretenessrepresent three of the six basic factors that Rubin(1980) found to underlie the variablespsychologists useto study verbal behavior.

MethodMaterials. Paivio et al.'s (1968) list of 925 nouns was used.

The dependent variable, familiarity, comes from a study inwhich subjects rated printed familiarity on a 7-point scale(Paivio, Note I) using a procedure sirnilar to Paivio (1968). Theindependent variables included associative frequency (fromTable 1), concreteness (Paivio et al., 1968), length in letters, andfrequency (Kuöera & Francis, 1967; Thorndike & Lorge, 1944).Two measures of frequency were included to help insure thatany effects of associative frequency could not be attributOO tosampling errors in one of the frequency counts. For theassocia­tive frequency andfrequency measures, logarithms to thebase 10were taken after all Os were replaced by .5s. For the Thorndike­Lorge count, AA and A words were assigned their customaryvalues of 100and 50, respectively.

ResultsThe multiple regression equation on familiarity, in

beta weights, using the above measures, is familiarity =.38 (Kuöera & Francis, 1967) + .37 (Thorndike & Lorge,

90 RUBIN

1944) + .19 (associative frequency) + .04 (concrete­ness) + .09 (length) (n =925, r = .816). If the wordswith an associative frequency of 0 are not included, theequation becomes: familiarity = .35 (Kuöera &Francis) + .25 (Thorndike & Lorge) + .30 (associativefrequency) - .02 (concreteness) + .10 (length) (n = 460,r = .736). The importance of each of the objectivefrequency counts is reduced by having both in theanalysis. If only the Kuöera and Francis count is used asa measure of objective frequency, the regression equa­tion becomes familiarity = .61 (Kuöera & Francis) + .27(associative frequency) + .08 (concreteness) + .05(length) (n =925, r = .789), with all words used. Foronly the words with associative frequency greater than0, the equation becomes familiarity = .50 (Kuöera &Francis) + .35 (associative frequency) - .004 (con­creteness) + .08 (length) (n = 460, r = .716). If thewords in these equations were considered as independentobservations, the effects of associative frequency wouldbe significant at the .001 level in a11 of the aboveanalyses. Thus, associative frequency appears to be amajor contributor to people's judgments of familiarity.In fact, the partial correlation of familiarity withassociative frequency, holding both frequency measuresconstant, is .214 for all 925 nouns and .306 for thosewith associative frequencies greater than O.

The effect of concreteness, noted by Galbraith &Underwood (1973), appears quite sma11 in this sample,using multiple regression. A multiple regression onfamiliarity, using only the two frequency measures andconcreteness, yields familiarity = .43 (Kuöera & Francis,1967) + .41 (Thorndike & Lorge, 1944) + .06 (concrete­ness) (n = 925, r = .805). Thus, even with associativefrequency removed, the effect here is different thanwould be expected from Galbraith and Underwood. Thisdifference is difficult to understand but may be dueto differences in method. Farniliarity, here, is defmedby a rating scale, whereas Galbraith and Underwood'sresult is based on paired comparisons of high- andlow-concreteness words.

The correlations between familiarity and the Kuöera­Francis (1967) and Thorndike-Lorge (1944) measuresused here were .750 and .759, respectively. The correla­tions reported by Shapiro (1969) for a magnitude­estimation measure of farniliarity were between .920 and.958, whereas Carro11's (1971) magnitude estimationproduced a correlation of .929 for a group of 13 normalsubjects and a correlation of .974 for a group of 15 lexi­cographers. One reason for this difference might be thedifference between using a 7-point rating scale and mag­nitude estimation (Stevens, 1975). Another reason mightbe that the range of frequency of the words used byShapiro and by Carro11 extends over 2.3 more log unitsthan Paivio et a1.'s (1968) nouns do. If this range isreduced by eliminating words at the extremes of Carro11'svalues, however, his correlation for normal subjectsdrops only from .929 to .906, making the difference inmethod appear to be the more important factor.

The lower correlation between familiarity and fre­quency used in this study leaves more variance free to beexplained by other variables, including associative fre­quency. The lower correlation, however, does notexplain why associative frequency is as successful as it is.Any noise introduced by the methods used need not besystematically related to associative frequency. Associa­tive frequency should be successful only if it accountsfor reliable variance in the dependent variables, which isnot accounted for by the other variables included in theanalyses performed.

GENERAL DISCUSSION

Two main substantive claims have been made:(l) Associative frequency is a good measure of the avail­ability of isolated words, and (2) associations are notsymmetrieal. Support for the first claim comes from thesuperior predictions of recall by associative frequencyin an earlier study (Rubin, 1980) and from the observa­tions in this study that high associative frequency wordsare easier to recall, are judged to be more familiar, areharder to recognize has having oecurred on a list, andattract more false alarms when used as foils ina recogni­tion experiment. All but the last observation have beenshown to hold when the effects of length in letters,imagery, and meaningfulness are excluded, and theeffects of frequency are either excluded or minimized.

Support for the second claim that associations arenot symmetrical comes from comparing associative fre­queney and meaningfulness. Associative frequency is thenumber of associations going to a word, whereas mean­ingfulness is the number of associations coming from aword. If associations were symmetrieal for any givenword, these two values would be the same and the twovariables would function equivalently. The values turnout to be different, as shown by the correlations given,and the variables function in different ways. Associativefrequency is a better predictor of which words will leadto easy leaming in a paired associate task when the asso­ciative frequency values are taken from the responsemembers. Meaningfulness is a better predictor for thestimulus member. Associative frequency has predictivevalue in recall that is independent of meaningfulness andcan affect reca11 and recognition when meaningfulness isheld constant. One implication of this asymmetry is thatin an associative network in which the nodes are words,the number of links going to a word is not equal to thenumber of links coming from a word, an impossiblesituation unless the links are directiona1.

One might view associative frequency as a variable inneed of explanation rather than as an explanation initself. A sirnilar criticism could be made, however, of anyvariable used to predict recall. One could ask, forinstance, what causes a word to be highly imageable. Onthe positive side, associative frequency, unlike many ofour independent variables, is not a rating scale, but acount of observed behavior. Although one can wonder

why some words come to mind more frequently, it isvery much like wondering why some words are writtenmore frequently. That is, at present it is hard to thinkof many concepts that are more basic than associativefrequency and could thus provide a satisfactory explana­tion of it.

REFERENCE NOTE

1. Paivio, A. Imagery ratings and other norms for 1,448 words.Unpublished manuscript, Univenity of Western Ontario, 1982.

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NOTE

I. A note about the meaning of two of the central terms ofthis paper needs to be made. The meaning of availability is usedin the sense of Asch and Ebenholtz (1962), Thomdike (1932),

92 RUBIN

Tversky and Kahneman (1973), and others, and refers to theease with which something comes to mind. It is, unfortunately,in conflict with Tulving and Pearlstone's (1966) distinctionbetween availability and accessibility: Accessibility comes closerto the present meaning of availability. The meaning of associa­tive frequency is taken from Ervin (963) and Howes (1957) andrefers to the number of times a word is given as an associate,rather than the number of associates a word has. Unfortunately,

it is in conflict with Mandler and Huttenlocher's (1956) andothers' use of associative frequency as a synonym, or nearsynonym, for meaningfulness.

(Received for publication May S,1982;revision aceepted August 6, 1982.)