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Response Biases in Survey Research

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1 Response Biases in Survey Research
Hans Baumgartner Smeal Professor of Marketing Smeal College of Business, Penn State University

2 Response biases when a researcher conducts a survey, the expectation is that the information collected will be a faithful representation of reality; unfortunately, this is often not the case, and survey researchers have identified many different sources of error in surveys; these errors may contaminate the research results and limit the managerial usefulness of the findings; if the response provided by a respondent does not fully reflect the “true” response, a response (or measurement) error occurs (random or systematic); response biases (systematic response errors) can happen at any of the four stages of the response process, are elicited by different aspects of the survey, and are due to a variety of psychological mechanisms;

3 The relationship between observed measurements and constructs of interest
The total variability of observed scores consists of trait (substantive), random error, and systematic error (method) variance. Random and systematic errors are likely to confound relation- ships between measures and constructs and between different constructs. They also complicate the comparison of means. T E M T1 T2 E2 E1 M1 M2

4 Outline of the talk Misresponse to reversed and negated items
Item reversal and negation, types of misresponse, and mechanisms Reversed item bias: An integrative model Eye tracking of survey responding to reversed and negated items Item grouping and discriminant validity Extreme and midpoint responding as satisficing strategies in online surveys Stylistic response tendencies over the course of a survey

5 The issue of item reversal
Should reverse-keyed items (also called oppositely-keyed, reversed-polarity, reverse-worded, negatively worded, negatively-keyed, keyed-false, or simply reversed items) be included in multi-item summative scales? If reversed items are to be used, does it matter whether the reversal is achieved through negation or through other means? What’s the link between reversal and negation, what types of MR result, what psychological mechanisms are involved, and how can MR be avoided?

6 Item reversal vs. item negation
authors often fail to draw a clear distinction between reversals and negations and use ambiguous terms such as ‘negatively worded items’, which makes it unclear whether they refer to reversed or negated items, or both; examples from the Material Values scale (Richins and Dawson 1992): It sometimes bothers me quite a bit that I can't afford to buy all the things I’d like. I have all the things I really need to enjoy life. I wouldn't be any happier if I owned nicer things.

7 Item negation items can be stated either as an assertion (affirmation) or as a denial (disaffirmation) of something (Horn 1989); negation is a grammatical issue; classification of negations in terms of two dimensions: what part of speech is negated (how a word is used in a sentence: as a verb, noun/pronoun, adjective, adverb or preposition/conjunction); how the negation is achieved (by means of particle negation, the addition of no, the use of negative affixes, negative adjectives and adverbs, negative pronouns, or negative prepositions);

8 negative prepositions Total
Negated by means of Part of speech Not, n’t No negative affixes negative adjectives and adverbs negative pronouns negative prepositions Total Verb [This salesperson does not make false claims.] n.a. dislike, disagree, etc. [I dislike food shopping very much.] reluctant, hesitant, never, rarely, seldom, hardly (ever), less, little, etc. [I seldom daydream.] without, instead of, rather than, etc. [This supplier sometimes promises to do things without actually doing them later.] 135 (44.7%) 5 (1.7%) 26 (8.6%) 171 (56.6%) Noun/ pronoun not everyone, not (only), etc. [I and my family will consume only certain brands, not others.] no object, no reason, no purpose, etc. [Clipping, organizing, and using coupons is no fun.] discomfort, disagreement, etc. [There is considerable disagreement as to the future directions that this hospital should take.] little, few, a lack of, none of the, not much, neither of, etc. [Many times I feel that I have little influence over things that happen to me.] no-one, nobody, none, nothing, etc. [Energy is really not my problem because there is simply nothing I can do about it.] except for, without, with the exception of, instead of, rather than, etc. [American people should always buy American-made products instead of imports.] 4 (1.3%) 17 (5.6%) 10 (3.3%) 14 (4.6%) 54 (17.9%) Adjective uninterested, dishonest, etc. [Most charitable organizations are dishonest.] rarely, less, etc. [I would be less loyal to this rep firm, if my salesperson moved to a new firm.] 55 (18.2%) 59 (19.5%)

9 negative prepositions Total
Negated by means of Part of speech Not, n’t No negative affixes negative adjectives and adverbs negative pronouns negative prepositions Total Adverb not much, etc. [After I meet someone for the first time, I can usually remember what they look like, but not much about them. no longer, etc. [Hard work is no longer essential for the well-being of society.] [I often dress unconventionally even when it's likely to offend others.] rarely, less, etc. [I feel I have to do things hastily and maybe less carefully in order to get everything done.] n.a. 2 (.7%) 1 (.3%) 3 (1.0%) 7 (2.3%) Preposition/ Conjunction not for, not (just) in, not (only) as, not until, not if (incl. unless), not because, etc. [I enjoyed this shopping trip for its own sake, not just for the items I may have purchased.] for nothing, etc. [I don't believe in giving anything away for nothing.] 10 (3.4%) 11 (3.7%) 151 (50.0%) 18 (6.0%) 68 (22.5%) 41 (13.5%) 5 (1.7%) 19 (6.3%) 302

10 Item reversal an item is reversed if its meaning is opposite to a relevant standard of comparison (semantic issue); three senses of reversal: reversal relative to the polarity of the construct being measured; reversed relative to other items measuring the same construct: reversal relative to the first item reversal relative to the majority of the items reversal relative to a respondent’s true position on the issue under consideration (Swain et al. 2008);

11 Integrating item negation and item reversal
Non-reversed Reversed Item negation Non-negated Regular (RG) items Talkative, enjoying talking to people Polar opposite (PO) items Quiet, preferring to do things by oneself Negated Negated polar opposite (nPO) items Not quiet, preferring not to be by oneself Negated regular (nRG) items Not talkative, not getting much pleasure chatting with people

12 Misresponse to negated and reversed items
MR → within-participant inconsistency in response to multiple items intended to measure the same construct; Item Consistent responding Misresponse to negated items (NMR) Misresponse to reversed items (RMR) Misresponse to polar opposites (POMR) Talkative (RG) A Not talkative (nRG) D Quiet (PO) Not quiet (nPO)

13 Using reversed and negated items in surveys: Some recommendations
although responding to reversed items is error prone, wording all questions in one direction does not solve the problem; negations should be employed sparingly, esp. if they do not result in an item reversal (note: negations come in many guises); polar opposite reversals can be beneficial (esp. at the retrieval stage), but they have to be used with care;

14 An integrative model of reversed item bias: Weijters, Baumgartner, and Schillewaert (2012)
two important method effects: response inconsistency between regular and reversed items; difference in mean response depending on whether the first item measuring the focal construct is a regular or reversed item; three sources of reversed item method bias: acquiescence careless responding confirmation bias

15 The survey response process (Tourangeau et al. 2000)
Attending to and interpreting survey questions (careless responding) Comprehension Retrieval Judgment Response Generating a retrieval strategy and retrieving relevant beliefs from memory (confirmation bias) Integrating the information into a judgment Mapping the judgment onto the response scale and answering the question (acquiescence)

16 Empirical studies (net) acquiescence and carelessness explicitly measured; confirmation bias modeled via a manipulation of two item orders in the questionnaire, depending on the keying direction of the first item measuring the target construct; three item arrangements: grouped-alternated condition (related items are grouped together and regular and reverse-keyed items are alternated); grouped-massed condition (items are grouped together, but the reverse-keyed items follow a block of regular items, or vice versa; dispersed condition (items are spread throughout the questionnaire, with unrelated buffer items spaced between the target items);

17

18 Results for Study 2 both NARS (gNARS = .33, p < .001) and IMC (gIMC = .31, p < .001) were highly significant determinants of inconsistency bias; the effect of NARS on inconsistency bias was invariant across item arrangement conditions, as expected; the effect of IMC did not differ by item arrangement condition; the manipulation of whether or not the first target item was reversed (FIR) did not affect responses (although in the first study the effect was significantly negative); the effect of FIR did not differ by item arrangement condition;

19 Eye tracking of survey responding (with Weijters and Pieters)
eye-tracking data may provide more detailed insights into how respondents process survey questions and arrive at an answer; eye movements can be recorded unobtrusively, and eye fixations show what respondents attend to while completing a survey;

20 Eye tracking study 101 respondents completed a Qualtrics survey and their eye movements were tracked; effective sample size is N=90; Design: each participant completed 16 four-item scales shown in a random sequence; the fourth (target) item on each screen was an RG, nRG, PO, or nPO item (4 scales each);

21 Areas of interest AOI1a to AOI1e AOI2a AOI3a AOI3b AOI2b AOI2c AOI3c
AOI2d AOI3a AOI3b AOI3c AOI3d AOI4a AOI5a AOI5b AOI4b

22 Fixation durations for various AOI’s Mean fixation duration
Mean fixation duration Percentage of total fixation duration aoi1 1.05 0.050 aoi1a 0.14 0.006 aoi1b 0.24 0.011 aoi1c 0.38 0.016 aoi1d 0.21 0.010 aoi1e 0.08 0.004 Aoi2 15.45 0.624 aoi2a 3.75 0.153 aoi2b 3.39 0.140 aoi2c 4.11 0.162 aoi2d 4.20 0.169 aoi5a 0.61 0.025 aoi5b (for nRG and nPO) 0.39 aoi3 4.88 0.212 aoi3a 1.40 0.061 aoi3b 1.12 0.048 aoi3c 1.15 0.049 aoi3d 1.20 0.053 aoi4 0.43 0.020 other areas 2.20 0.099 Total 24.01 1.000

23 Solutions for Fixed Effects
Determinants of total fixation duration for fourth item (logaoi23dplus1) Solutions for Fixed Effects Effect Estimate S. E. t Value Pr > |t| Intercept 0.6203 0.1601 3.87 0.0015 Survey completion time 0.0013 0.0002 8.66 <.0001 Screen sequence 0.0020 -2.65 0.0082 Number of words 0.0387 0.0112 3.46 0.0006 Reversal of item 0.0411 0.0185 2.23 0.0261 Negation of item 0.1249 0.0202 6.20 Use of a PO in the item 0.0605 0.0188 3.22 Note: These results are based on a mixed model with respondent and construct as random effects.

24 Determinants of misresponse
Solutions for Fixed Effects Effect Estimate S. E. t Value Pr > |t| Intercept 0.6418 0.0850 7.55 <.0001 Fixation duration for item (logaoi23plus1) 0.1394 0.0417 3.34 Reversal of item 0.0383 0.0184 2.08 0.0380 Negation of item 0.0159 0.0185 0.86 0.3912 Use of a PO in the item 0.1197 0.0187 6.40 Note: These results are based on a mixed model with dist=gamma and construct as a random effect.

25 Item grouping and discriminant validity (Weijters, de Beuckelaer, and Baumgartner, forthcoming)
question whether items belonging to the same scale should be grouped or randomized: grouped format is less cognitively demanding and often improves convergent validity; random format may reduce demand effects, respondent satisfacing, and carryover effects, as well as faking; effect of item grouping on discriminant validity: grouping of items enhances discriminant validity (Harrison and McLaughlin 1996); item grouping may lead to discriminant validity even when there should be none;

26 Method 523 respondents from an online U.S. panel
questionnaire contained the 8-item frugality scale of Lastovicka et al. (1999) and 32 filler items; frugality scale presented in two random blocks of 4 items each, with the 32 filler items in between Condition 1: vs Condition 2: vs within blocks item order was randomized across respondents;

27 Estimated models

28 Results COND Model MODEL ² DF CFI TLI SRMR RMSEA Cond 1 Two factors
Hypothesized model 53.82 19 .964 .946 .037 .083 Best of alternative permutations 198.13 .810 .720 .090 .188 Average of alternative permutations 221.84 .788 .687 .096 .200 One factor One-factor model 234.04 20 .776 .686 .095 Cond 2 43.67 .961 .943 .040 .071 88.24 .880 .823 .069 .120 129.93 .825 .743 .076 .151 140.83 .734 .154

29 Results (cont’d)

30 Results (cont’d) Condition 1 Condition 2 Factor 1
Average Variance Extracted (AVE) .54 .53 Composite Reliability (CR) .82 .81 Factor 2 .61 .40 .86 .71 Factors 1 and 2 Correlation Shared Variance (SV) .38

31 Extreme and midpoint responding as satisficing strategies in online surveys (Weijters and Baumgartner) when respondents minimize the amount of effort they invest in formulating responses to questionnaire items by selecting the first response that is deemed good enough, they are said to be satisficing; when respondents put in the cognitive resources required to arrive at an optimal response, they are optimizing (Krosnick 1991); the effectiveness of procedural remedies to prevent or at least reduce satisficing (MacKenzie & Podsakoff 2012) is limited; post hoc indices designed to identify satisficers often exhibit limited convergent validity and unambiguous cutoff values are often unavailable;

32 Satisficing in online surveys (cont’d)
online surveys are likely to contain data from respondents who are satisficing, but what will be the consequences? we review satisficing and related measures that have been proposed in the literature and propose a new measure called OPTIM; we investigate the effect of satisficing on two stylistic response tendencies (ERS and MRS) and we demonstrate that the direction of the relationship varies across individuals;

33 The concept of satisficing
the notion of satisficing is consistent with the view of people as cognitive misers (Fiske and Taylor 1991); satisficing is conceptually similar to carelessness, inattentiveness, insufficient effort responding, and content-nonresponsive, content-independent, noncontingent, inconsistent, variable or random responding; Krosnick (1991) argues that in weak forms of satisficing each of the four steps of the response process (comprehension, retrieval, judgment, response) might be compromised to some extent, whereas in strong forms of satisficing the second and third steps might be skipped entirely;

34 Measures of satisficing
Dedicated measures  Special items or scales are included in the questionnaire to measure satisficing No dedicated measures  Satisficing is inferred from respondents’ answers to substantive questions Direct measurement   Satisficing is assessed directly by measuring respondents’ tendency to minimize time and effort when responding to a survey Category 1  Self-reported effort (e.g., I carefully read every survey item). Category 2  Response time Indirect measurement Satisficing is assessed indirectly based on the presumed consequences of respondents’ attempts to minimize time and effort on the quality of responses Category 3  Quality of responses to special items or scales (e.g. bogus items, instructed response items) Category 4  Quality of responses to substantive questions (e.g., outlier analysis, lack of consistency of responses, excessive consistency of responses)

35 Measures of satisficing (cont’d)
a single-category measure is unlikely to assess satisficing adequately; direct measures of satisficing are desirable (esp. response time measures); bogus items and IMC’s have limitations; response differentiation for unrelated items might be a good outcome-based measure;

36 A new measure of satisficing
optimizing as the time-intensive differentiation of responses to items that are homogeneous in form but heterogeneous in content: OPTIM=log(TIME*DIFF) survey duration: input side of effort (indicator of the cognitive resources invested by a respondent); time taken to complete the survey (in minutes), rescaled to a range of 0 to 10; response differentiation: output side of effort (indicator of optimizing for heterogeneous items); DIFF = (f1+1)*(f2+1)*(f3+1)*(f4+1)*(f5+1), rescaled to a range of 0 to 10;

37 ERS and MRS as satisficing strategies
previous research suggests that both ERS and MRS may be used as satisficing strategies (even though ERS and MRS tend to be negatively correlated), although the empirical findings have not been very consistent; different respondents may use different satisficing strategies: some respondents may simplify the rating task by only using the extreme scale positions (resulting in increased ERS); others may refrain from thinking things through and taking sides (resulting in increased MRS);

38 Method two online studies with Belgian (n=320) and Dutch (n=401) respondents; in dataset A 10 heterogeneous attitudinal items and in dataset B Greenleaf’s (1992) ERS scale; these items were used to construct the ERS (number of extreme responses), MRS (number of midpoint responses) and DIFF measures; survey duration was measured unobtrusively; use of a multivariate Poisson regression mixture model of ERS and MRS on OPTIM;

39 Model

40 Regression estimates by class
DV Intercept B SE 90% CI DATASET A Class 1 (46.3%) ERS 2.64 -.54 .10 [-.70, -.38] Extreme responders MRS -3.08 1.39 .20 [1.06, 1.72] Class 2 (47.1%) -1.04 .90 .11 [.72, 1.08] Yeah-sayers -.53 .53 [.35, .71] Class 3 (6.7%) -7.25 3.04 .83 [1.67, 4.41] Midpoint responders 2.39 -.49 .14 [-.72, -.26] DATASET B Class 1 (43.7%) -1.73 1.13 .12 [.93, 1.33] 2.59 .08 [-.66, -.40] Class 2 (35.7%) -.41 .88 .39 [.24, 1.52] .24 .44 .25 [.03, .85] Class 3 (20.6%) 2.91 -.48 [-.89, -.07] -.40 .57 .15 [.32, .82]

41

42 Dataset A Dataset B

43 Discussion OPTIM as an unobtrusive measure that integrates several aspects of optimizing/satisficing; across two distinct samples, three satisficing segments emerged: extreme responders midpoint responders acquiescent responders OPTIM is useful if a continuous measure of satisficing is required, but it may be less useful as a screening device for careless responders;

44 Stylistic response tendencies over the course of a survey (Baumgartner and Weijters)
three perspectives on stylistic responding: nonexistence of response styles (complete lack of consistency); instability of response styles (local consistency); stability of response styles (global consistency); Weijters et al. (2010) showed that the nonexistence of response styles was strongly contradicted by the empirical evidence for both extreme responding and acquiescent responding; there was a strong stable component in the ratings; and there as a weaker local component (as indicated by a small time-invariant autoregressive effect);

45 Unresolved questions how do stylistic response tendencies evolve over the course of a questionnaire? prior research has only considered the effect of stylistic responding on the covariance structure of items or sets of items and has ignored the mean structure; are there individual differences in both the extent to which stylistic response tendencies occur across respondents and the manner in which stylistic response tendencies evolve over the course of a survey? prior research has not emphasized heterogeneity in stylistic response tendencies across people;

46 ALT model

47 Integrated ALT model for NARS and ERS

48 Method data from 523 online respondents;
each participant responded to a random selection of eight out of 16 possible four-item scales shown on eight consecutive screens in random order; eight separate response style indices were computed for both (net) acquiescence response style or NARS (i.e., respondents’ tendency to express more agreement than disagreement) and extreme response style or ERS (i.e., respondents’ disproportionate use of more extreme response options); the design guarantees that there is no systematic similarity in substantive content over the sequence of eight scales across respondents;

49 Results Estimate SE T p 95% confidence interval iERS .918 .019 49.03
Means iERS .918 .019 49.03 < .001 [ , ] sERS -.009 .003 -2.77 .006 [ , ] iNARS 3.298 .027 123.59 [3.246, ] sNARS -.019 .005 -3.77 [ -.029, ] Variances .105 .012 9.00 [ .082, .128] .001 .000 2.49 .013 [ .000, .002] .155 .024 6.38 [ .108, .203] 1.30 .195 [-.001, .003] Correlations iERS with sERS -.312 .120 -2.60 .009 [-.547, -.077] iERS with iNARS .491 .082 5.98 [ .330, .651] iERS with sNARS -.189 .204 -.93 .352 [-.588, .210] iNARS with sNARS -.583 .132 -4.42 [-.842, -.325] sERS with iNARS -.074 .172 -.43 .669 [-.411, .264] sERS with sNARS .129 .388 .33 .740 [-.632, .889]

50 NARS and ERS trajectories

51 Distribution of the slope factor for ERS

52 Response distributions on the first and the last screen of the questionnaire

53 Backup slides

54 A comprehensive model of measurement error
yijt = ijt + ijt jt + ijt + ijt yijt  a person’s observed score on the ith measure of construct j at time t jt  a person’s unobserved score for construct j at time t ijt  systematic error score ijt  random error score ijt  coefficient (factor loading) relating yijt to jt ijt  intercept term (additive bias) systematic error random error

55 Empirical data we analyzed items from volumes 1 through 36 of JCR (1974 till the end of 2009) and volumes 1 through 46 of JMR (1964 to 2009); we included all Likert-type scales for which the items making up the scale were reproduced in the article and factor loadings or item-total correlations were reported; total of 66 articles in which information about 1330 items measuring 314 factors was provided; of the 1330 distinct items in the data set, 608 came from JCR and 722 from JMR;

56 Item reversal (cont’d)
in our data set of 1330 items, between 83 and 86 percent of items were nonreversed (depending on the definition of reversal); the proportion of factors (or subfactors in the case of multi-factor constructs) that do not contain reversed items was 70 percent; only 8 percent of factors (out of 314 factors) were composed of an equal number of reversed and nonreversed items (i.e., the scale was balanced);

57 Cross-classification of negation and reversal
Reversal relative to Polarity of construct Polarity of first item Dominant keying direction Total Non- reversed Reversed Balanced No negation(s) 71.1% 8.7% 71.0% 70.3% 5.2% 4.2% 79.7% Negation(s) 11.7% 15.4% 4.9% 13.7% 2.9% 3.7% 20.3% 82.8% 17.4% 86.4% 13.6% 84.0% 8.1% 7.9% 100.0%

58 Theoretical explanations of MR: Reversal ambiguity and comprehension
Rs may not view antonyms as polar opposites [POMR]; contradictories vs. contraries: Antonym reversals can be contradictories or contraries, depending on whether they are bounded or unbounded (Paradis and Willners 2006); Negation reversals are contradictories if the core concept is the same; the situation is more complicated for the negation of bounded and unbounded antonyms; simultaneous disagreement with contraries is more likely when items are worded extremely (McPherson and Mohr 2005); “Buddhism’s ontology and epistemology appear to make East Asians relatively comfortable with apparent contradictions” (Wong et al. 2003, p. 86) [RMR];

59 Theoretical explanations of MR: Comprehension
Careless responding (Schmitt and Stults 1985): respondents fail to pay careful attention to individual items and respond based on their overall position on an issue [RMR]; more likely when a reversed item is preceded by a block of nonreversed items; Remedies: make Rs more attentive and/or explicitly alert them to the presence of reversed items; use balanced scales, alternate the keying direction, and disperse the items;

60 Theoretical explanations of MR: Comprehension (cont’d)
Reversal ambiguity: Rs may not view antonyms as polar opposites [POMR]; “Buddhism’s ontology and epistemology appear to make East Asians relatively comfortable with apparent contradictions” (Wong et al. 2003, p. 86) [RMR]; contradictories vs. contraries: Negated statements are contradictories; Antonyms can be contradictories or contraries, depending on whether they are bounded or unbounded (Paradis and Willners 2006); simultaneous disagreement is more likely when items are worded extremely (McPherson and Mohr 2005);

61 Theoretical explanations of MR: Comprehension (cont’d)
Remedies: use more sophisticated procedures to identify appropriate antonyms (formulate linguistic contrasts in two stages; see Dickson and Albaum 1977); may be particularly useful in cross-cultural research; bounded antonyms have to be pretested and unbounded antonyms have to be used with care; extreme statements should be avoided;

62 Theoretical explanations of MR: Retrieval
Item-wording effects: Confirmation bias (Davies 2003; Kunda et al. 1993); Directly applicable to antonymic reversals; For negation reversals, confirmation bias can lead to MR if a non-negated polar opposite schema is readily available (Mayo et al. 2004); Remedies: Use polar opposite reversals to get richer belief samples, even though they may increase apparent MR; Negation reversals have few retrieval benefits;

63 Theoretical explanations of MR: Retrieval
Positioning effects: Dispersed PO items reduce carryover effects and can increase coverage, but the task is more taxing for Rs and internal consistency may suffer; Item similarity may determine whether Rs engage in additional retrieval when items are grouped together; Remedies: The use of dispersed antonyms should encourage the generation of distinct belief samples; Avoid very similar (negated) statements when items are grouped;

64 Theoretical explanations of MR: Judgment
Item verification difficulty (Carpenter and Just 1975; Swain et al. 2008): MR is a function of the complexity of verifying the truth or falsity of an item relative to one’s true beliefs, which depends on whether the item is stated as an affirmation or negation [NMR]; Remedies: Negations are problematic because they increase the likelihood of making mistakes (remember there are many types of negations); Negated polar opposites are most error-prone; Mix of regular and PO reversals should be best;

65 Item verification difficulty
MR Negation Affirmation Truth value False True

66 Theoretical explanations of MR: Response
Acquiescence: Rs initially accept a statement and subsequently re-consider it based on extant evidence; the first stage is automatic, the second requires effort (Knowles and Condon 1999) [RMR]; Remedies: Although response styles are largely individual difference variables, situational factors may be under the control of the researcher (e.g., reduce the cognitive load for Rs); Problems with online surveys;

67 Theoretical explanations of MR: Response (cont’d)
Asymmetric scale interpretation: the midpoint of the rating scale may not be the boundary between agreement and disagreement for Rs (esp. if the response categories are not labeled; cf. Gannon and Ostrom 1996) [RMR]; Remedies: Use fully labeled 5- or 7-point response scales;

68 Careless responding respondents do not always pay attention to the instructions, the wording of the question, or the response options before answering survey questions because of satisficing; respondents may form expectations about what is being measured and respond to individual items based on their overall position concerning the focal issue, rather than specific item content; this can result in inconsistent responding to reverse-keyed items; esp. likely when constructs are labeled and when grouped-massed item positioning is used; measurement: instructional manipulation checks (IMC), bogus items, and self-report measures of response quality response times post hoc response consistency indices (too much or too little)

69 Examples of IMC’s Between 14% and 46% of respondents failed this test in Oppenheimer et al. (2009)

70 Examples of IMC’s About 7% of respondents (out of over 1000) failed this test (see Oppenheimer et al. 2009)

71 (Dis)Acquiescence tendency to agree (ARS) or disagree (DARS) with items regardless of content (agreement or yea-saying vs. disagreement or nay-saying bias); leads to response inconsistency for reversed items; Measurement: simultaneous (dis)agreement with contradictory statements; (dis)agreement with many heterogeneous items; net acquiescence as the relative bias away from the midpoint; different arrangements of the items in the questionnaire should have no differential effect on acquiescent responding;

72 Confirmation bias when respondents answer a question, they tend to activate beliefs that are consistent with the way in which the item is stated (positive test strategy, inhibition of disconfirming evidence); this leads to a bias in the direction in which the item is worded (e.g., Are you introverted? vs. Are you extraverted?) and differences in mean response; the effect of the keying direction of the first item on confirmation bias should be strongest in the grouped-massed condition and weakest in the dispersed condition;

73 Example item with 4 negations
Top management in my company has let it be known in no uncertain terms that unethical behaviors will not be tolerated.

74 Revised Life Orientation Test (LOT)
In uncertain times, I usually expect the best. I’m always optimistic about my future . Overall, I expect more good things to happen to me than bad. If something can go wrong for me, it will. I hardly ever expect things to go my way. I rarely count on good things happening to me.

75 Weijters, Baumgartner, and Schillewaert (forthcoming)
models in which method effects are included generally yield a much better fit to the data than models in which only substantive factors are included; it is often difficult to clearly distinguish between different method effect specifications on the basis of statistical criteria; the psychological processes causing method effects are frequently left unspecified; although method factors have been related to a variety of other psychological constructs, the choice of these other constructs often seems ad hoc;

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79 Weijters, Baumgartner, and Schillewaert (forthcoming)
models in which method effects are included generally yield a much better fit to the data than models in which only substantive factors are included; it is often difficult to clearly distinguish between different method effect specifications on the basis of statistical criteria; the psychological processes causing method effects are frequently left unspecified; although method factors have been related to a variety of other psychological constructs, the choice of these other constructs often seems ad hoc;

80 Responses to bogus items (Meade and Craig, 2012)
% strongly disagree or disagree responses (1,2) % other responses (3-7) I sleep less than one hour per night. 90 10 I do not understand a word of English. I have never brushed my teeth. 92 8 I am paid biweekly by leprechauns. 80 20 All my friends are aliens. 82 18 All my friends say I would make a great poodle. 73 27

81 I feel satisfied with the way my body looks right now.
Strongly Disagree (1) Disagree (2) Neither Agree nor Disagree (3) Agree (4) Strongly (5) I feel satisfied with the way my body looks right now. I am satisfied with my weight. I am pleased with my appearance right now. I feel attractive. I don’t feel attractive. I feel ugly. I don’t feel ugly.

82 Neither Agree nor Disagree (3)
Strongly Disagree (1) Disagree (2) Neither Agree nor Disagree (3) Agree (4) Strongly Agree (5) A product is more valuable to me if it has some snob appeal. The government should exercise more responsibility for regulating the advertising, sales and marketing activities of manufacturers. Most retailers provide adequate service. I feel attractive. I don’t feel attractive. I feel ugly. I don’t feel ugly.

83 OPTIM


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