Graduate Theses and Dissertations
Iowa State University Capstones, Theses and
Dissertations
2017
Negation-induced forgetting: Is there a
consequence to saying “no”?
Rachel Elizabeth Dianiska
Iowa State University
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Recommended Citation
Dianiska, Rachel Elizabeth, “Negation-induced forgetting: Is there a consequence to saying “no”?” (2017). Graduate Theses and
Dissertations. 15293.
https://lib.dr.iastate.edu/etd/15293
Negation-induced forgetting: Is there a consequence to saying “no”?
by
Rachel Elizabeth Dianiska
A thesis submitted to the graduate faculty
in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE
Major: Psychology
Program of Study Committee:
Christian A. Meissner, Major Professor
Jason C.K. Chan
Gary L. Wells
The student author and the program of study committee are solely responsible for the
content of this thesis. The Graduate College will ensure this thesis is globally accessible
and will not permit alterations after a degree is conferred.
Iowa State University
Ames, Iowa
2017
Copyright © Rachel Elizabeth Dianiska, 2017. All rights reserved.
ii
TABLE OF CONTENTS
Page
LIST OF FIGURES ………………………………………………………………………………………
iv
LIST OF TABLES
………………………………………………………………………………………..
v
ABSTRACT……………………………….
……………………………………………………..
vi
CHAPTER 1
INTRODUCTION ………………………………………………………………..
1
The Negation Effect
…………………………………………………………………………………
2
Negation in Attention
……………………………………………………………………………….
4
Negation in Memory ………………………………………………………………………………..
6
Overview of the Current Studies
………………………………………………………………..
7
CHAPTER 2
EXPERIMENT 1 ………………………………………………………………….
9
Method
……………………………………………………………………………………………
9
Experiment 1A Results …………………………………………………………………………….
13
Experiment 1B Results …………………………………………………………………………….
15
Discussion ……………………………………………………………………………………………
16
Table and Figures
…………………………………………………………………………………….
17
CHAPTER 3
EXPERIMENT 2 ………………………………………………………………….
19
Method
……………………………………………………………………………………………
19
Experiment 2A Results …………………………………………………………………………….
22
Experiment 2B Results …………………………………………………………………………….
23
Combined Samples Analysis …………………………………………………………………….
24
Discussion ……………………………………………………………………………………………
25
Table and Figures
…………………………………………………………………………………….
27
CHAPTER 4
EXPERIMENT 3 ………………………………………………………………….
28
Method
……………………………………………………………………………………………
30
Results
……………………………………………………………………………………………
33
Discussion ……………………………………………………………………………………………
38
Table and Figures
…………………………………………………………………………………….
39
CHAPTER 5
GENERAL DISCUSSION …………………………………………………….
42
Replicability of the Negation Effect …………………………………………………………..
42
iii
Theoretical Mechanisms Leading to Negation …………………………………………….
44
Practical Implications of the Negation Effect in Memory ……………………………..
47
Conclusions and Figures …………………………………………………………………………..
48
REFERENCES …………………………………………………………………………………………….
49
APPENDIX A. EXPERIMENT 1 QUESTIONS ………………………………………………
52
APPENDIX B. EXPERIMENT 1 RKG INSTRUCTIONS ………………………………..
54
APPENDIX C. EXPERIMENT 2 INSTRUCTIONS
…………………………………………
55
APPENDIX D. EXPERIMENT 2 QUESTIONS ………………………………………………
56
APPENDIX E. EXPERIMENT 3 QUESTIONS
……………………………………………….
57
APPENDIX F. EXPERIMENT 3 RKG INSTRUCTIONS
…………………………………
59
APPENDIX G. IRB APPROVAL FOR EXPERIMENTS
………………………………….
60
iv
LIST OF FIGURES
Page
Figure 1 Experiment 1 Procedure
…………………………………………………………………..
18
Figure 2 Effect Size Graph for Mayo et al. (2014), Experiment 1A,
and Experiment 1B …………………………………………………………………………
18
Figure 3 Effect Size Graph for Experiment 2
…………………………………………………..
27
Figure 4 Graph of Negation Effect by Number of Alternatives Interaction …………
41
Figure 5 Forest Plot of Negation Effect Sizes
………………………………………………….
48
v
LIST OF TABLES
Page
Table 1 Means for Final Test Measures in Experiment 1A (False Rejection,
Accurate Recognition) and Experiment 1B (proportion recalled)
………….
17
Table 2 Means for Final Memory Test Errors in Experiment 2
…………………………
27
Table 3 Means for Final Test Measures in Experiment 3,
Load-Absent Condition
……………………………………………………………………
39
Table 4 Means for Final Test Measures in Experiment 3,
Load-Present Condition …………………………………………………………………..
40
vi
ABSTRACT
The negation effect refers to the cognitive detriment associated with correctly
saying “no” (a negation), compared to correctly saying “yes” (an affirmation). A recent
study has shown this detriment for item memory following the negation of a feature of an
item (Mayo, Schul, & Rosenthal, 2014). This research examines the replicability of the
negation effect using the original paradigm, as well as an adapted list-learning paradigm.
Participants studied a set of objects and were then asked questions about features of
objects that elicited “yes” or “no” responses. After a filler task, participants completed a
final memory test during which they indicated whether a given object label was present
or not present during the study phase.
Experiment 1 failed to conceptually replicate the negation-induced forgetting
effect present in Mayo et al. (2014) using a list-learning paradigm. Experiment 2 was a
pre-registered replication, and the negation effect was successfully replicated using the
original stimulus and test materials from Mayo et al. (2014). Experiment 3 successfully
replicated the negation effect using a list-learning paradigm, and found that the
magnitude of the negation effect is influenced by the number of alternatives suggested by
a feature statement.
1
CHAPTER I: INTRODUCTION
Imagine the following scene: one afternoon, you hear through your window what
you think may be gunshots. Turning around to look, you see one man lying on the ground
behind a car, and another man holding a gun a few feet away. You make a note of the
gunman’s description in your head: tall, average build, white t-shirt and jeans, black
baseball cap. While you are phoning the incident in to the police, the man with the gun
grabs a backpack from the trunk of the car and runs away. The police arrive a few
minutes later, and once the area is secured you are asked to make a statement. A detective
asks you a simple question: “Was the baseball cap blue?” Your answer to this question –
a “yes” or “no” – may later influence what you remember about the event.
Cognitive psychologists have long been aware of the limitations and malleability
of human memory (e.g., Loftus, 2005). An understanding of these limitations has
informed decades of research on how memory can be altered or falsely recollected, as
well as how memory retrieval can be improved in applied contexts (e.g., interviewing of
witnesses and suspects). However, advances in interviewing techniques have only been
accompanied by a partial understanding of how the type of question a person is asked can
influence his or her memory. Studies have assessed the influence of mnemonic
techniques (the Cognitive Interview; Geiselman, Fisher, MacKinnon, & Holland, 1986),
generating verbal descriptions (the verbal overshadowing effect; Schooler & Engstler-
Schooler, 1990), suggestive questioning and social influence (e.g., Garven, Wood,
Malpass, & Shaw, 1998; Hope, Ost, Gabbert, Healey, & Lenton, 2008), and interference
due to selective retrieval of event information (e.g., Camp, Wesstein, & Bruin, 2012;
Chan, Thomas, & Bulevich, 2009) on subsequent memory for an event or suspect. One
2
aspect of questioning that has been overlooked involves the potential influence of
negation on subsequent memory – that is, the cognitive detriment associated with
correctly saying no to a question (negation), compared with correctly saying yes to a
question (affirmation).
Prior studies have primarily situated negation in a context of lexical
comprehension, focusing on how negations themselves are communicated and
understood; however, memory researchers utilizing manipulations requiring a “yes” or
“no” response have also observed differences in performance based upon the response
given. The finding that a person’s memory or comprehension can be differentially
influenced based upon whether one responds affirmatively or negatively appears to have
been demonstrated consistently, yet has garnered little attention. The following studies
attempted to replicate this negation effect in memory, and to further identify factors that
may moderate the effect. Specifically, these studies examined the influence of affirmative
or negative responses to forced-choice, yes-no statements related to a feature of an object
(e.g., “The glass was empty”) on subsequent memory for the object of the question. In
this context, the negation effect encompasses a comparative memory impairment based
upon an accurate response of “no” to questions about features of studied objects, rather
than an accurate response of “yes.”
The Negation Effect
The negation effect has been studied since the 1960s, particularly in the area of
psycholinguistics. In this context, negations are represented as sentences describing how
a situation is not (e.g., Susan does not bake cookies), whereas affirmations are
represented as sentences describing the actual situation (e.g., Stephen tidied up his
3
drawers). The nature of how negations are represented and accessed, as well as how
accessibility influences understanding and inference-making has been explored. Using
lexical comprehension and sentence verification tasks, a “negation effect” has been
shown when participants more quickly and more accurately verify affirmative statements
(Gough, 1965; Wason, 1961). Negated words and phrases have also been associated with
decreased accessibility and slower response times (Engelkemp & Hormann, 1974; Kaup
& Zwann, 2003; MacDonald & Just, 1989; Meyer, 1975).
Despite years of research, the manner in which negations are represented in
memory is still debated. Two models of negation representation that have been explored
include the schema-plus-tag model and the fusion model. The schema-plus-tag model
proposes that a negated message is first processed using an affirmative meaning and is
then negated (e.g., Mayo, Schul, & Burnstein, 2004). For example, this model suggests
that a negated statement such as “not red” would first be processed as “red” with the
negation operator subsequently added to the representation. The fusion model, in
contrast, proposes that the meaning of the negated phrase is the result of merging of the
negation operator with the affirmed meaning. The phrase “the door is not open” would
thus be represented as the fusion of “not” and “open”, or “closed.” These competing
models of representation yield different implications for associations that are activated
when the negated statement is processed, as well as for long-term retention of the
meaning of the negated statement.
To compare the two models, Mayo and colleagues (2004) examined the
inferences participants made as different negations and affirmations were processed.
Participants encoded affirmed target sentences (e.g., “Tom is a tidy person”) or negated
4
target sentences (e.g., “Tom is not a tidy person”) and then determined whether a probe
sentence describing a behavior (e.g., “Tom forgets where he left his car keys”) fit the
meaning of the target sentence. Negations in this study were presented three ways:
semantically negated, as sentences with negation operators; visibly negated, with a red
background that signaled that a sentence should be negated; or dually negated, as
sentences with negation operators that were also displayed on a red background. The
behavioral probes could be consistent with, inconsistent with, or irrelevant to the meaning
of the target sentence. A baseline condition was included for comparison, wherein people
first saw the behavioral probe and then assessed the congruency of the affirmed or
negated sentences. Compared to this baseline, people were quicker to respond when the
probe meaning was consistent with an affirmed target phrase, as well as when the probe
meaning was inconsistent with a negated target phrase. Processing a negated message
first as an affirmation in the schema-plus-tag model would activate associations that are
inconsistent with the negated meaning. Thus, Mayo and colleagues (2004) suggested that
the facilitation of incongruent associations with negated sentences in this study supports
the schema-plus-tag model (e.g., Hasson & Glucksberg, 2006). In addition to
representations, research into negation has extended to other areas of cognition, including
attention and memory.
Negation in Attention
Negations are a crucial element of communication, for instance in directing
attention away from or administering instructions not to do something. The use of
negation as a communication device can sometimes itself lead to communication errors.
Consider the classic studies of thought suppression: when people were instructed, “don’t
5
think about white bears,” sometimes that instruction led people to paradoxically think
about white bears (Wegner, Schneider, Carter, & White, 1987). Recently, Maciuszek
(2013) examined the nature of negations in commands (e.g., “don’t pay attention to
[target],”) in memory and comprehension. Attention focus, as measured by the amount of
details recalled about the target, was found to be greater for people who received the
negation order, compared to people in control groups who either were not told anything
about the target, or who were not ordered to pay attention to the target. In other words,
when participants were instructed not to pay attention to something, attention was drawn
to the object to a greater extent.
Orenes, Beltrán, and Santamaría (2014) used a visual world paradigm to
investigate how negations are understood and represented based on the situational context
and number of available alternatives. The visual world paradigm allowed for both images
and verbal information to be presented simultaneously, and eye movement data was
collected to determine the focal point of attention. Four images of colored figures (red,
green, blue, yellow) were displayed while a statement was presented. Initial statements
that were presented to participants manipulated the situation in which figures would
appear: either with two alternatives (“The figure could be red or green”) or with multiple
alternatives (“The figure could be red, or green, or blue, or yellow”). Subsequent
statements were ether phrased as affirmations (“The figure was red”) or negations (“The
figure was not red”). When the initial statement set up a context in which multiple
alternatives were present, people tended to direct their attention to the object of a negated
sentence. That is, participants who were presented with the negated statement “the figure
was not red” would focus on the red figure, rather than any of the other alternate colored
6
figures. On the other hand, when a situation implied only two alternatives, participants’
attention was directed to the intended color conveyed by the statement. That is, when
presented with the negated statement, “the figure was not red,” participants focused on
the figure of the other color present in the scenario. The attentional component of
negation thus appears to be sensitive to the number of alternatives suggested by the
statement, and this may differentially influence what is remembered following that
negation.
Negation in Memory
Manipulations using yes-no questions to assess memory are prevalent throughout
the cognitive literature. While the impact of negation on subsequent memory for word
lists has been documented in classic studies of the levels of processing effect (Craik &
Tulving, 1975), the implications for object or event memory have only recently been
explored (Mayo, Schul, & Rosenthal, 2014). In their original demonstration of the levels
of processing effect, Craik and Tulving (1975) required participants to respond “yes” or
“no” to prompts that systematically manipulated the level of semantic processing for a
list of words – varying, for example, the physical structure of the word (e.g., “Is the word
in capital letters?”); whether or not the target word rhymed with another (e.g., “Does the
word rhyme with ___?”); or whether or not the target word fit a given category (e.g., “Is
the word a type of ____?”) or syntactical structure (e.g., “Would the word fit the
sentence: ‘_____’?”). Across several experiments, Craik and Tulving noted a consistent
effect of response type (yes or no), with the pattern of means suggesting that words
associated with a “yes” response were better remembered compared to words associated
with a “no” response. Positive responses allowed for the encoding prompts to be better
7
integrated with the target items, resulting in a more elaborate memory trace.
More recently, Mayo, Schul, and Rosenthal (2014) demonstrated that correctly
negating a feature of an object can subsequently impair memory for that object, compared
to affirming a feature of the object. Mayo and colleagues examined a “negation-induced
forgetting” effect based on the nature of a rehearsal (affirmative or negative). Participants
were shown a video tour of an apartment and were later asked questions about features of
items that were shown in the video. The initial memory test in Experiment 1 was
composed of 16 questions, eight eliciting “no” responses and eight eliciting “yes”
responses. After a 20-minute unrelated filler task, subjects completed a final recognition
test for the objects they saw in the video. Overall, when feature questions elicited correct
“no” responses, participants were less likely to remember the object (e.g., “ashtray”) on
the final memory test, compared to when feature questions elicited “yes” responses (d =
0.53 [0.19, 0.87]1). Mayo and colleagues termed this comparative memory impairment
“negation-induced forgetting.” That is, when subjects thought about an object and
negated it, the representation of that object was subsequently less accessible. Given the
potential applicability of this negation impairment to domains like education and forensic
interviewing, I sought to examine the replicability and robustness of the effect.
Overview of the Current Studies
In three experiments, I examine the replicability of the negation effect in memory.
In Experiment 1, I attempt a conceptual replication of Mayo et al. (2014) using a list-
learning paradigm. In Experiment 2, I conduct a pre-registered direct replication of Mayo
1 The effect size was provided by the primary author, and confidence intervals for effect
sizes were constructed using ESCI software (Cumming, 2012).
8
et al. (2014) using the original stimulus and test materials. In Experiment 3, I return to the
list-learning paradigm to examine two potential moderators of the negation effect:
memory load at encoding, and the number of alternatives suggested by a test statement.
9
CHAPTER 2: EXPERIMENT 1
The “negation-induced forgetting” effect seen in Mayo et al. (2014) prompted a
replication attempt using a list-learning paradigm. Subjects in the first of Mayo and
colleagues’ (2014) experiments studied all of the stimuli (i.e., everyday household
objects) by watching a video of a computer-simulated tour of an apartment. After
watching the video, subjects provided “yes” and “no” responses to statements describing
features of the objects that they had seen in the apartment. Following a 20-minute
unrelated filler task, subjects then completed a final object recognition test.
The following experiment examined the replicability of the negation effect when
using a single-item presentation list-learning paradigm. Subjects in the current study were
shown images of simple objects and presented with statements about features of those
objects that elicited “yes” or “no” responses. To conceptually replicate the encoding
experience of subjects in the Mayo paradigm, subjects in Experiment 1 studied a series of
objects in sequence and were then immediately tested on the feature statements (see
Figure 1). Following a 20-minute filler period, subjects were administered a final test
involving either object recognition (Exp. 1A) or free recall (Exp. 1B).
Method
Participants. A total of 84 subjects (42.9% male) completed Experiment 1 for
partial course credit. Mean age was 18.86 (SD = 2.28). In Experiment 1A, 49 subjects
completed a final recognition test. In Experiment 1B, 35 subjects completed a final free
recall test. Three subjects were excluded from the analysis in 1B due to a failure to
follow instructions.
10
Materials and Design. Stimuli included 32 images of simple objects retrieved
from the Massive Visual Memory Stimuli dataset (Brady, Konkle, Alvarez, & Oliva,
2013). Object images were selected to vary based upon the features of both an attribute
(e.g., color) and state (e.g., open/closed). The feature statements for each studied object
were administered via pre-recorded audio files that involved a female speaker reading the
statements aloud. Each statement recording was between 2500ms and 3000ms.
Statements that were presented to participants can be found in Appendix A.
This study employed a within-subjects design manipulating response to feature
questions on an initial memory test (yes or no)2. Object memory was assessed via
performance on a final memory test. In Experiment 1A, subjects indicated that an object
was “Present” or “Not Present” in the study phase on a final recognition test. In
Experiment 1B, subjects freely recalled all of the items that they could remember seeing
in the study phase.
Procedure. This study was divided into three phases: a study phase, an initial test
phase, and a final test phase. A schematic representation of the procedure can be found in
Figure 1. Prior to the first phase, subjects provided informed consent and received
instructions about the experiment. Specifically, they were instructed that they would
study a set of simple objects and be asked questions about features of those objects at a
later time. They were not informed that they would take a final test with regard to the
2 This condition was independent of another study manipulation in which the yes/no
questions were presented immediately prior to encoding an image, similar to the
paradigm used by Craik & Tulving (1975). For subjects in that pre-encoding condition,
there was no significant negation effect in either recognition (d = .02 [-.28, .23]) or recall
(d = .45 [-.14, 1.03]). For the purpose of this paper, I focus the discussion on this post-
encoding manipulation of negation, consistent with the Mayo et al. (2014) paradigm.
11
images that they studied. The remaining instructions and tasks were presented to subjects
via E-Prime 2.0TM.
Subjects were randomly assigned to a condition prior to arriving for the
experiment. In the study phase, subjects studied the full set of 32 objects for 250ms each
with a 1000ms ISI. Following the presentation of all object images, subjects completed
the initial test phase, which was comprised of feature statements that described correct or
incorrect attributes of the studied objects. These feature statements were randomly
divided into “yes” or “no” responses, and counterbalanced so that each object was
equally associated with both responses across all conditions.
Immediately following the study phase, all subjects completed an unrelated 20-
min filler task that required them to locate sequences of numbers vertically, horizontally,
or diagonally, similar to a word search. Next, subjects completed a final object memory
test. In Experiment 1A, this final test was a recognition test: subjects were shown simple
object labels (e.g., “highlighter”) and were asked to indicate whether that object was
present or not present in the first part of the study. The final recognition test was
comprised of 64 object labels – half of these object labels corresponded to the 32 studied
objects from the first phase of the experiment (and thus elicited correct “Present”
responses), while the other half corresponded to new, unstudied objects (and thus elicited
correct “Not Present” responses). The order of presentation for test items was determined
randomly for each subject. For each item, subjects were also asked to provide a
confidence estimate and phenomenological memory (i.e., remember-know-guess)
judgment. Confidence was assessed using a 1 to 5 scale, with 1 corresponding to “not
sure at all” and 5 corresponding to “definitely sure” that the object was or was not
12
studied. Subjects were provided instructions with respect to remember/know/guess
responses and were asked to choose between “I (would have) recollected seeing the
object”, “The object is (not) familiar to me”, and “I am guessing” for each decision on
whether an object was studied.3 Specific instructions can be found in Appendix B. The
order of presenting confidence and memory basis judgments was counterbalanced such
that half of the subjects first rated confidence and then provided the memory basis
judgment, while the other half first provided a memory basis judgment and then the
confidence rating.
The final test in Experiment 1B involved a free recall test. Subjects were given as
much time as they needed to list objects recalled from the first part of the experiment.
Subjects were prompted twice to recall all of the objects they could remember studying.
Free recall responses were coded by a research assistant blind to the images used in the
study. A response was counted as correct/present if the research assistant could discern
what object was being named, even if the label was not a perfect fit. For instance, the
terms “marker” and “highlighter” would both be considered as correct for “highlighter”.
After completing the final memory test, subjects were debriefed and dismissed from the
study.
Given my interest in replicating the negation-induced forgetting effect in Mayo et
al. (2014), I will report Bayes Factors (BF10) in addition to the traditional null hypothesis
significance tests (NHST). Bayes factors enable the comparison of evidence strength for
two models: one in which there is no significant negation effect (the null hypothesis,
3 Subjects provided these responses for both “old” and “new” responses. In the results, I
focus on the phenomenological memory judgments for only correct “old” responses.
13
Model 0), and one in which there is a significant effect (the alternative hypothesis, Model
1). The BF10 factor will be used to express the probability of the data given the alternative
hypothesis (Model 1) relative to the probability of the data given the null hypothesis
(Model 0). However, when this value is less than 1, I will invert it for interpretation. For
the subject-level effects, I will use the effect size for Mayo et al. (2014) Experiment 1 as
provided by the primary author, d = 0.53 [0.19, 0.87], as the prior distribution. For the
item-level analyses, I will use the standard Cauchy prior of 0.707 to calculate BF10. The
magnitude of BF10 can be used to interpret the strength of the evidence: a factor of 0 to 3
is considered anecdotal evidence; 3 to 10 is considered substantial evidence; 10 to 100 is
considered strong evidence; while a factor greater than 100 is considered decisive
evidence (Jeffreys, 1961).
Results – Experiment 1A
Initial Memory Test. The initial memory test was used to elicit “yes” and “no”
responses from participants. It consisted of 32 statements pertaining to features of objects
that were studied. Half of the statements described correct features of the objects and
required “yes” responses; the other half described incorrect features of the objects and
were correctly answered with “no” responses. A paired-samples t-test was used to assess
the influence of initial memory test response (yes, no) on the proportion of accurate
responses to the feature statements. Subjects were similarly accurate for statements
requiring a “yes” response (M = .72, SE = .02) and for statements requiring a “no”
response (M = .70, SE = .02), t(48) = 1.52, p = .14, d = 0.17 [-0.05, 0.40].
Final Memory Test. Two outcome measures were of primary interest: (1)
conditionalized errors on the final memory test, and (2) phenomenological memory bases
14
for accurately recognized objects on the final memory test. For each person, the
proportion of conditionalized errors made on the final memory test was calculated.
Conditionalized errors refer to items that were associated with a correct response on the
initial memory test, but were responded to as “Not Present” on the final memory test.
Proportions of Remember and Know responses were also calculated for objects correctly
recognized as having been present in the first part of the experiment. Know responses
were corrected for independence of the two processes by dividing the number of Know
responses (K) by the opportunities to respond Know (1 – R; see Yonelinas & Jacoby,
1995).
A paired-samples t-test was used to assess the influence of initial memory test
response (yes, no) on the proportion of errors on the final memory test (i.e., studied items
that were correctly answered on the initial test but were not recognized as having been
studied in the first part of the experiment). Although numerically more errors were made
following “no” responses (M = .10, SE = .02) than following “yes” responses (M = .07,
SE = .01), a statistically significant negation effect was not observed, t(48) = 1.49, p =
.14, d = .27 [-.09, .62].
To further examine the null effect, a Bayesian paired-samples t-test was
conducted using JASP software (JASP Team, 2016). An estimated BF10 of 0.54 suggests
that the data were 1.85 times more likely under the null hypothesis, which is considered
weak evidence. In addition to these subject-level analyses, an item-level analysis was
conducted to determine if a negation effect was present across the 32 target items. When
examined at an item-level, there was a marginally significant negation effect, t(31) =
2.03, p = .05, d = 0.38 [.01, .74]. An estimated BF10 of 1.15 suggests that the data were
15
1.15 times more likely under the alternative hypothesis on an item-level. Again, this
Bayes Factor is considered weak or anecdotal evidence.
The second measure of interest involved the basis upon which subjects correctly
recognized objects. A paired-samples t-test was used to assess the influence of initial
memory test response (yes, no) on the proportion of accurately recognized objects based
on remembering and knowing. No differences in recollection responses were observed
following “yes” (M = .85, SE = .02) vs. “no” responses (M = .84, SE = .03), t(48) = .48, p
= .63, d = 0.07 [-0.22, 0.35]; nor were differences observed in familiarity responses
following “yes” responses (M = .55, SE = .07) vs. “no” responses (M = .58, SE = .07),
t(48) = .39, p = .70, d = 0.06 [-0.37, 0.25].
Results – Experiment 1B
Initial Memory Test. A paired-samples t-test was used to assess the influence of
initial memory test response (yes, no) on the proportion of accurate responses to the
feature statements. Subjects were similarly accurate for statements requiring a “yes”
response (M = .71, SE = .02) and for statements requiring a “no” response (M = .69, SE =
.02), t(31) = .93, p = .36, d = 0.18 [-0.20, 0.55].
Final Memory Test. A paired-samples t-test was used to assess the influence of
initial memory test response (yes, no) on the proportion of studied objects correctly
recalled. This measure was conditionalized for accuracy on the initial test, such that only
objects correctly answered with “yes” or “no” on the initial test were included in the final
proportion recalled. Subjects recalled fewer objects associated with a “no” response (M =
.29, SE = .02) than those associated with a “yes” response (M = .32, SE = .03); however,
this difference was not significant, t(31) = 1.04, p = .31, d = .21 [-.14, .56]. An estimated
16
BF10 of 0.39 suggests that the data were 2.58 more likely under the null hypothesis. An
item-level analysis was used to determine if a negation effect was present across the 32
target items. The item analysis revealed a significant negation effect, t(31) = 2.28, p =
.03, d = -0.81 [-1.52, -.08]. More objects were correctly recalled after a “yes” response
(M = .59, SE = .04) than after a “no” response (M = .41, SE = .04). An estimated BF10 of
1.79 indicates that the data provided weak evidence for the alternative hypothesis on an
item-level.
Discussion
The present studies failed to find a significant negation effect for either
conditionalized errors on a final recognition test (1A) or for conditionalized accuracy on
a final free recall test (1B). A similar effect size for the negation effect was observed for
both recognition, d = .27 [-.09, .62] and recall, d = .21 [-.14, .56]. While these effects fall
within the confidence intervals of the original effect produced by Mayo et al. (2014)
[0.19, 0.87], they are at the lower end of the distribution and were about half the size
original effect (d = 0.53). Bayes factors (BF10 = 0.54 and 0.39, respectively) suggested
only weak evidence in favor of the null hypothesis. Despite the presence of a negation
effect in an item-level analyses, the lack of subject-level effects takes precedence in the
interpretation of the negation effect’s non-significance (e.g., Raaijmakers,
Schrijnemakers, & Gremmen, 1999).
17
Table 1
Means for final test measures in Experiment 1A (false rejection, accurate recognition)
and Experiment 1B (proportion recalled)
After “yes”
After “no”
Measure
Mean
SD
Mean
SD
False Rejection
Proportion Errors
.07
.10
.10
.11
Confidence
2.76
1.00
2.61
1.02
Accurate Recognition
Response Latency
1525
314
1612
431
Confidence
4.68
.28
4.59
.28
Remember
.85
.15
.84
.18
Know (Corrected)
.55
.48
.58
.47
Proportion Recalled
Accurate
.32
.15
.29
.13
18
Figure 1. Graphic representation of the procedure used in the present Experiment 1 to
conceptually replicate the procedure used in Experiment 1 of Mayo, Schul, & Rosenthal
(2014).
Figure 2. Effect sizes with 95% confidence intervals for Mayo et al. (2014), Experiment
1A (recognition test), and Experiment 1B (recall test).
-0.2
0
0.2
0.4
0.6
0.8
1
Mayo et al. (2014)
Experiment 1
Exp. 1
Recognition Test
Exp. 1
Recall Test
Effect Size (Cohen’s d)
