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Technical Manual

2010

©2010 Glowinkowski™ International LimitedGlowinkowski International

2 Contents

Table of Contents

CONTENTS PAGE

Technical Manual................................................................................................................................................. 3

Construct Validity ....................................................................................................................................... 7

Internal Correlation ................................................................................................................................... 11

Internal Reliability ..................................................................................................................................... 13

Test-Retest Reliability ............................................................................................................................... 14

References ..................................................................................................................................................15

Glowinkowski Predisposition Indicator (GPI™) - V2.1

©2010 Glowinkowski™ International Limited. All rights reserved.

Glowinkowski International, Ltd.5 St Peter’s Court, Middleborough, Colchester, Essex, CO1 1WD

www.glowinkowski.com

©2010 Glowinkowski™ International Limited

Glowinkowski Predisposition Indicator (GPI™)

3Technical Manual

Technical Manual

Early psychological research

Work on personality can be traced back to Hippocrates, the Greek physician, who spoke of four personality types, namely Choleric, Melancholic, Sanguine and Phlegmatic.

Sigmund Freud was the first psychologist to investigate personality scientifically. Freud’s research is much criticised, most notably for the fact that it was largely based on case study evidence using a non-representative sample. It is also often argued that Freud’s theory is not testable so not falsifiable and consequently does not meet a fundamental requirement for scientific theory. Nevertheless, Freud’s work on the stages of development, Id, Ego and Superego and the different levels of consciousness still strike much debate today and have formed the basis for many subsequent theorists’ work.

Since Freud, much of the subsequent personality research has focused on the identification of traits. Traits are mechanisms within individuals that shape the way they react in different situations. Traits are often said to summarise past behaviour and predict future. In scientific, experimental terms, research has attempted to identify the basic personality traits that reliably describe and account for the individual differences in personality between people.

Throughout the 20th century there was a great deal of disagreement as to the specific number of traits, or factors, that exist and the literature reveals a raft of different researchers that claim to have found the answer to this question. At one end of the spectrum Cattell identified 16 factors of personality whilst Eysenck (1967) initially claimed there were two, Neuroticism and Extraversion, before subsequently adding a third, Psychoticism.

Disagreement about the number of separate factors of personality prevailed until mid way though the second half of the 20th century. More recent studies by McCrae and Costa (1987) have indentified five core factors. This work is in agreement with that of earlier researchers such as Thurstone (1934) and Fiske (1949) and the research we have been conducting since the early nineties. We see a five factor representation of personality as the most valid model, as do many other research institutions and industry professionals around the world. Consistently, across different genders, cultures, languages and age ranges, five factors are now accepted as the largest number of separate, uncorrelated dimensions of personality. These factors are as follows:

1. �Extraversion – Assertive, active, excited, gregarious, energetic, outgoing

2. �Agreeableness – Trusting, modest, compliant, generous, kind, sympathetic

3. Attainment�(often�referred�to�as�Conscientiousness) – Ordered, planned, thorough, achievement-striving

4. Emotionality�(this�includes�the�concept�of�Neuroticism) – Anxious, self-conscious, impulsive, tense, worrying

5. Cognition�(often�referred�to�as�Openness�to�Experience) – Ideas, curious, imaginative, insightful

These five factors provide trait descriptions at the highest level only. There is a wealth of data which underpins them.

The conclusions to be drawn from research around these five factors are as follows:

• It is an overarching and robust model that has been developed over a large number of years and has stood the test of time

• It is a model that has broad applicability when used effectively:

– It provides a common language across cultures – It is comprehensive thus allowing exploration of

personality with other concepts, e.g. motivation, competency behaviours

– It has efficiency and simplicity making it easier to use

Up until the development of the five factor model, investigations into the validity of personality assessment for industrial/organisational application produced less than encouraging results. In fact Guion and Gottier (1965) concluded “… it is difficult to advocate with a clear conscience the use of personality measures in most situations as a basis for making employment decisions” (pg 160). However, the development of the five factors framework together with more advanced statistical techniques made possible through a rapid acceleration in computer technology has painted a more encouraging picture in recent years. Meta-analyses, combining a number of studies’ findings looking at the correlation between the five factors and outcome measures, i.e. job performance, have revealed favourable results in support of personality measurement (for an example, see Barrick and Mount, 1991).

Such studies are not without their shortcomings however. Quality of performance measurement is consistently cited as a problem, as are the generality of the results. This is perhaps in the favour of personality measurement because where personality inventories are selected to match the requirements of a job analysis, predictive validity rises (Tett, Jackson and Rothstein, 1991). Similarly, where there is more specific job performance data, the amount of variance in performance which the five factors account for grows (see Hogan & Holland, 2003). On a downside however, if personality is more predictive of performance outcomes in one situation than another then the generalisation and therefore application of the research has to be questioned. With this in mind it is necessary to think critically about


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the whole concept of predictive validity in personality measurement and therefore, whether personality inventories should be used at all in selection situations. As behaviour is the driver of performance i.e. what you do determines what you get - but is a function of both the personality of an individual and the situation they find themselves in - personality is of limited use alone for predicting performance. Even if the situational parameters are well specified, other elements of the individual such as their motives, values and beliefs will shape the way they behave.

Perhaps Guion and Gottier (1965) were right to some extent with the point that personality measurement should not be used in employment situations. Although research suggests a link between personality and performance is now more favourable than in the mid-sixties, predictive validity is perhaps in the general sense, absurd. Predictive validity does not begin to mean anything until performance is considered more specifically. It makes sense to say therefore, that given certain personality profiles, certain tasks within an individual’s role will be more/less comfortable to perform. This is likely to have an impact on whether an individual does some role required things as much as they should.

Why we developed the GPI™

Although we harboured doubts (indeed we still do) as to the concept of predictive validity within the five factor model in terms of its ability to predict delivered behaviours in a general sense, we still saw this model as a highly valid and practical way of presenting and describing personality.

We found however find that the current ways of assessing the five core dimensions of personality did not match up to our requirements. There were several tools available on the market but none of them were able to tick all of the boxes and meet all of our needs. We therefore set out to develop our own tool – the Glowinkowski Predisposition Indicator (GPI™) – which was able to fulfil the requirements that we had. The problems with existing inventories for assessing personality and therefore the reason for developing the GPI™ fit into five categories

1. Terminology and language2. Conceptualisation3. Statistical validity and reliability4. Practicality5. The distinction of predisposition, other aspects of

personality and behaviour

1. Terminology and language

Predispositions and behaviour are separate things. If a predisposition does play itself out in behaviour, it is possible that some predispositional profiles may be less positive than others. However, as mentioned above, predisposition and behaviour are different things and therefore, in simple terms, there is no right or wrong in predispositions. Not only did we find that in several of the available measures the distinction

between predisposition and behaviour was not clear, and we shall return to this point more thoroughly in point five, but the measures also described some predispositions as more favourable than others. If predispositions are considered as bi-polar, it is not then right to attribute favourability to either side or hold one pole above the other. Both poles of a predisposition have their strengths and weaknesses and furthermore, if a predisposition does play itself out in behaviour, a behavioural strength in one situation may be a behavioural weakness in another.

Whilst some measures used pejorative terminology at the output stage, others used socially desirable terminology at the input stage. According to Dunnette (1972), one in seven people ‘fake good’ in personality tests. In other words, they try to create a profile which they think will be more favourable than their real profile for the specific context their profile will be considered in. One in seven is a relatively high proportion of test takers and one that interpreters should be aware of but, unfortunately, accept as a reality. Whilst such faking behaviour relies on the test taker making an accurate analysis of the ‘right’ profile and then being able to pick the questions correctly which assess the predispositions they want to portray - two things which are by no means easy - it was our view that certain tests made such faking behaviour easier. To give an example, if individuals are being assessed for their suitability for a sales role, asking if that person enjoys trying to persuade people is unlikely to get a negative response, whether it actually is the case or not. In this situation, one in seven people faking is, no doubt, a conservative estimate.

2. Conceptualisation

It is our view that if the measure used is going to be applied to an industrial/organisational/business setting, presenting the output in language which is directly applicable to this world is a must. Building on this, using terminology which is concrete, definable and immediately applicable to a client’s role is hugely important. Getting this right comes partly from the rationale for the development of a test – was it developed for business application, or clinical application, or for some other reason? If a test was not developed for industry/organisations/business and then did not ‘cut its teeth’ in this setting during the initial development and validation phase, it is unlikely the language will match the need. Furthermore, without an understanding of organisations during the development of a measure – i.e. where and how the measure will be applied - the language may appear to be right but in practice miss the point.

In our experience, several tests fell into the trap of having conceptual issues. Where the labels used to describe the poles of a dimension were not immediately apparent in their meanings, valuable time was spent in the feedback session explaining what the dimension was assessing when the objective of the session was to talk about what the profile meant and how it applied to the client.



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3. Statistical specifications

Validity, i.e. whether a test measures what it purports to measure, is the key concept. We felt we encountered too many feedback sessions where the data shocked the client – it was at odds with data they had received in the past. Other individuals could simply not see how a profile related to them. This wasn’t a situation we wanted to be in as consultants.

Outputs of some tests revealed distributions in the dimensions that we were not comfortable with either. The validity of tests was thrown into question where the population was strongly skewed towards one end of a dimension without a good explanation as to why this should be the case. In other cases, this situation was apparent in males but not in females, in one culture but not in another and similar questions of validity were sparked within us.

4. Practicality

Personality ‘types’, where an individual is either one type or another, are immensely useful in a feedback session. In exchange for the simplicity of type however you lose the richness of dimensions.

In dimensions of personality you have a level of detail unavailable in types, but too often it means trying to give a feedback session by pointing to where an individual sits on a dimension, twenty or thirty times. Feedback sessions become descriptions of profiles rather than interpretations. Making links between data points is difficult even for expert interpreters and as a client, having a profile which is of any use after the feedback session is extremely unlikely.

In short, there are pros and cons associated with both type and dimensional representations of personality. When it comes to having to make the choice between the feedback methods, we got the feeling that you can’t have your cake and eat it. Have our cake and eat it was exactly what we wanted to do however.

Presentation of data is extremely important, both for digestion at an individual and team level. We found that some presentation profiles were designed for individual feedback sessions - a context in which they worked well - but the same data could not then be aggregated for use in a team feedback session. Where team data was presented effectively for team feedback sessions, there wasn’t enough detail in the data to make a truly valuable intervention.

As mentioned above, in addition to the inability to use detailed data outputs in a team setting, we also found that detailed outputs were difficult to interpret. Lots of dimensions spread across a series of pages was a common occurrence in outputs and something we saw as a flaw. Test outputs are of the greatest use when the data points can be linked together. Outputs should be looked at as a whole – this was extremely difficult with many detailed outputs we came across.

A final problem with practicality we often encountered builds on the conceptualisations piece, where we often found

clients were unable to link their profile to their everyday life. Clients found the data interesting but were left with a feeling of “so what?” Partly because of the way the language was used in the labelling of the data points, partly because of the way the output was presented, individuals struggled to see the relevance to their leadership, their team and their organisation.

5. Predisposition and Behaviour

Predispositions are preferred behaviours, things people have a preference for and feel comfortable doing. Actual behaviour on the other hand is delivered, it can be seen, it is concrete and although it is influenced by predisposition, the two are not one and the same. Although this boundary is a clear one, we found too often that tests blurred it, confusing the difference between two separate things and presenting them as the same.

It is perfectly possible to measure predispositions, motivation, competencies, values and any number of other things in one questionnaire, but they cannot then be presented back without distinction as if they are the same. This is a practical problem as it causes confusion on the part of the client and a theoretical problem as it confuses distinctly different factors. Not only are predispositions different from behaviour and therefore, competencies, they also give no reliable indication as to ability and therefore, competence. In addition to these problems, confusing predisposition with values and motivation confuses the former which is relatively stable with the two latter concepts which are far more transient and susceptible to changes. Predispositions hold true for a lifetime but values and motivation can change daily.

We felt that whilst the problems mentioned above were not present across each available test – each test had its strengths where certain factors did not fall foul to these problems; there was not a test available which did well in all of these five areas. The rationale for developing the GPI™ was therefore to meet all of these needs in one measure.

Developing the GPI™

In developing the tool there were three key considerations:

• An identification of the key concepts underpinning each of the five dimensions – the sub-dimensions

• An easy self-reporting method that captured each of those concepts

• An easy method by which the data would be presented back

A key consideration in the development of the GPI™ was to ensure that the data was presented in a way that makes for ease of comprehension. It was also considered important to get a large amount of information presented in a way that would meet the needs of those who prefer detail as well as those who prefer the big picture. The physical presentation


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had to aid and abet purposeful and constructive dialogue between the person providing the interpretative feedback and the recipient.

As a result, the data is presented in three overarching models:

• Problem Solving and Implementation Style

This presents data relating to the dimensions of Cognition (Problem Solving i.e. thinking), and Attainment (Implementation Style).

Cognition explores ideas, insightfulness, decision making, in other words, the way we approach thinking. Attainment explores conscientiousness, delivery and thoroughness, i.e. attention to detail in delivery.

As a result, there was considered a natural logic in combining these factors in terms of presentation style. Thus the model provides data to stimulate discussion concerning how we think about ideas and takes decisions, i.e. Problem Solving, and how we then turn that thinking into our subsequent actions and deliverables, i.e. Implementation.

• Communications and Interpersonal style

This draws together data from the factors of Extraversion and Agreeableness.

The logic of this linkage again sits in the detail of the model, namely that Extraversion explores drawing energy from being outgoing and engaging with others, whilst Agreeableness explores our propensity to collaborate or be more single minded when interacting with other people.

Thus there is sense in modelling our level of excitement derived from interacting with others and our expectations from such interactions.

• Feelings and Self-control

This model examines the factor of Emotionality which includes Neuroticism.

The logic of examining this dimension separately concerns its more sensitive aspects and the fact that it presents some fundamentally pejorative concepts. This is overcome by the

vocabulary used and the subtle manner that this enables some very personal issues to be discussed.

GPI™ Construction

Nineteen bipolar dimensions were developed, each assessed by between eight and ten items. Examining each facet from a number of angles helps avoid acquiescence, nay-saying and lying. Individual items were tested for relevance and reliability. The total number of items in the list after three versions was 182.

The item style is completing the sentence. For each item, the beginning is “I am the sort of person who…”, and each item is then followed with “thinks…”, “likes…”, “feels…”, “is…” etc. The answer style is a sliding five-point scale of agreement, from “Strongly Disagree” (1), “Disagree” (2), “Neither agree nor disagree” (3), “Agree” (4), “Strongly Agree” (5).

The raw data from the items is added to get the raw facet scores, and these are matched against normalised data and converted to the standard ten (sten) scale. In feedback, the sten is changed somewhat so that each score is from one to five on the relevant pole of the dimension. For example, an individual may score a sten of 10 for Anxiety. However, since Anxiety was made bipolar, ranging from relaxed to tense, the feedback for the test shows a score of ‘Tense 5’. Similarly a score of Anxiety at sten 1 to gives a score of ‘Relaxed 5’ as shown in the figure below. This method also ensures positive feedback; a high or a low sten score now translates to the high end of the dimension. Any subject with a mid range score will not put negative inference on the lower number quoted in their feedback because it means they are in the middle.

The split-sten scale also proves useful in situations of graphical representation of behaviour, allowing two dimensions to be compared as axes to produce four quadrants, where the individual’s score of ±1 to 5 for each dimension are converted to x and y coordinates and plotted.

1 2 3 4 5 6 7 8 9 10

Relaxed

Anxiety

STEN

5 4 3 2 1 1 2 3 4 5

Tense



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construct Validity

Method

125 clients participated in the GPI™ validity study. All participants were from Glowinkowski International’s consulting client base. Participants completed three psychometric instruments:

• The GPI™

• The NEO Personality Inventory

• The Myers Briggs Type Indicator (MBTI)

NEO and MBTI were first correlated against eachother, in order to prove the strong sympathy between NEO dimensions and MBTI types as has been hypothesised. They were secondly correlated against the GPI™, to show its validity in accordance with the construct method, as well as to highlight the differences between the three tests.

It was expected that the correlations for dimensions would be stronger with NEO than with MBTI equivalents in this analysis, as each dimension was constructed from its two distinct sub-dimensions to make one linear scale.

Conversely, when the dimension pairs were examined as discrete, separate items, it was expected that the correlation would be higher against the relevant MBTI pairs.

As the GPI™ is made up of more dimensions than either the MBTI or the NEO, it was expected that some sub-dimensions within a dimension would not correlate, or that they would have a much lower significance of correlation with either test.

This was because the GPI™ dimension in question measured some quality that neither the MBTI nor NEO have the capacity to allow for.

Results and Discussion

In Table 1, the GPI™ correlates largely and highly significantly where it has been predicted. Emotionality is not linked in any way to the MBTI types, which do not have the capability to measure separate facets of emotion outside of its type boundaries. Extraversion correlates very strongly positively with Myers Extraversion, and strongly negatively with Myers introversion. Cognition with Sensing-Intuitive (SN) and Attainment with Judging-Perceiving (JP) were both predicted. The Agreeableness vs. Feeling-Thinking (FT) is lower than expected.

Down the five factors of the NEO, strong correlations are apparent between Emotionality and Neuroticism, Extraversion and Extraversion, Cognition and Openness, Agreeableness and Agreeableness and Attainment and Conscientiousness (Table 2). It is also particularly notable here that Cognition seems also to correlate well with NEO Extraversion – this is interesting as it links in with good evidence showing that high scoring extraverts are more radical in their thinking.

Correlations are strong for Extraversion, as shown overleaf (Table 3). The only facet that does not correlate highly is Hedonism, which in retrospect makes a great deal of sense,

Domains

Emotionality Extraversion Cognition Agreeableness Attainment

MBTI Introversion 0.11 -.71*** -.31* 0.09 0.12

Extraversion -0.16 .72*** .36** -0.08 -0.15

Sensing 0.08 -.27* -.63*** 0.02 .25*

Intuitive -0.05 .37* .57*** -0.08 -.30*

Feeling 0.02 0.08 0.01 .39** 0.21

Thinking 0.07 -0.13 0.01 -.37** -0.17

Judging -0.09 -.32* -.35** 0.16 .54***

Perceiving 0.12 .30* 0.28 -.24* -.51***

NEO Neuroticism .70*** -.35** -0.13 -0.05 0.02

Extraversion -.47*** .75*** .49*** -0.03 0.03

Openness -0.12 .28* .53*** 0.02 -0.02

Agreeableness -0.19 -0.19 -0.18 .75*** .42**

Conscientiousness -.35** 0.03 -0.03 0.22 .65***

*p<0.1 **p<0.01 ***p<0.001Table 1: Correlations between the five domains of the GPI™ and the main scales of MBTI and NEO


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Anxiety Hostility Optimism Self-Esteem Impulsiveness

MBTI Introversion .23* 0.08 .40** 0.15 -.53***

Extraversion -.27* -0.09 -.47*** -0.16 .50***

Sensing 0.04 0.09 0.12 0.09 -0.07

Intuitive -0.11 -0.06 -0.13 -0.05 0.1

Feeling 0.05 -0.14 -0.14 0.13 0.18

Thinking -0.03 .27* 0.15 0.05 -0.21

Judging 0.17 -0.05 -0.03 -0.03 -.40**

Perceiving -0.19 0.14 0.06 0.03 .40**

NEO Neuroticism .62*** .45** .37** .70*** .20***

Extraversion -.53*** -0.21 -.67*** -.44** .35**

Openness -0.05 -0.03 -.30* -0.04 0.03

Agreeableness 0.09 -.45*** -0.11 0.13 -.36**

Conscientiousness -0.03 -.37** -.23* -.26* -.34*

*p<0.1 **p<0.01 ***p<0.001Table 2: GPI™ Emotionality sub domains and the scales of MBTI and NEO

Sociability Assertiveness Hedonism Social Poise

MBTI Introversion -.66*** -.41** -0.16 -.62***

Extraversion .62*** .37** .27* .61***

Sensing -0.16 -0.2 -0.02 -.29*

Intuitive 0.09 .24** 0.05 .29*

Feeling .25* -0.17 0.08 0.11

Thinking -.27* 0.13 -0.02 -0.21

Judging -0.25 -0.16 -.29* -0.15

Perceiving 0.18 0.21 .29* 0.11

NEO Neuroticism -0.1 -.27* -0.01 -0.47

Extraversion .68*** .48*** 0.11 .67***

Openness 0.17 0.14 0.08 .33*

Agreeableness -.41** 0.03 -0.04 -0.19

Conscientiousness -0.11 0.15 -.32* .26*

*p<0.1 **p<0.01 ***p<0.001Table 3: GPI™ Extraversion sub domains and the scales of MBTI and NEO



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as the Fun Loving/Serious Minded concept is not included in ether MBTI or the NEO.

Assertiveness also shows some correlation with Neuroticism – this is attributed to the need for high self esteem in one’s self in order to be assertive with others.

All facets of Agreeableness (GPI™) correlate strongly with Agreeableness (NEO). However, only Affiliation has any level of correlation at all with TF. This is the heart of Tough versus Tender-minded, where the need for love and acceptance of others overrides logic in those with high Feeling. It is interesting that TF does not really have a place for the facets of Trusting/Suspicious, but does illustrate the point that the TF scale is more about emotionality than behaviour – a subject with high feeling would have difficulty being suspicious.

All facets of Attainment correlate with Conscientiousness. However, only Implementation correlates strongly to JP. Achievement and Conscientiousness do so to a lesser extent, but it is clear that JP covers mostly only spontaneity and planning, and has little to cover attention to the detail of the task itself. The strong correlation of Conscientiousness (GPI™) to Agreeableness (NEO) is possibly attributable to the fact that individuals who are Cursory can often be curt in their interactions too, whereas those who show high Conscientious would be more careful to interact regularly or appear warm, even when strongly individualist. Implementation shows a strong correlation with SI – this is easier to explain as high spontaneity would almost certainly lean towards Sensing and the more offbeat approach to life and work.

Change Orientation Information Processing Decision Making

MBTI Introversion -.29* -0.16 -.29*

Extraversion .35** 0.2 .30*

Sensing -.52*** -.67*** -.36**

Intuitive .50*** .66*** .24*

Feeling -0.08 -0.09 .23*

Thinking 0.1 0.1 -.24*

Judging -.25* -.26* -.37**

Perceiving 0.18 0.2 .34*

NEO Neuroticism -.35** -0.1 .28*

Extraversion .53*** 0.31 .26*

Openness .45*** .60*** .26*

Agreeableness -0.17 -0.19 -0.09

Conscientiousness 0.15 -0.18 -0.15

*p<0.1 **p<0.01 ***p<0.001Table 4: GPI™ Cognition sub domains and the scales of MBTI and NEO


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Table 6: Attainment

Affiliation Trust Conformity Modesty

MBTI Introversion -0.11 -0.04 0.18 .24*

Extraversion 0.09 0.11 -.22* -.23*

Sensing -0.02 -0.2 0.22 0.07

Intuitive -0.03 0.17 -.23* -0.16

Feeling .54*** 0.2 .32* 0.18

Thinking -.50*** -0.22 -.24* -.22*

Judging 0.03 -0.05 .29* .25*

Perceiving -0.07 -0.02 -.32* -.34*

NEO Neuroticism 0.04 -.22* 0.17 -0.13

Extraversion 0.15 0.07 -0.15 -0.16

Openness 0.01 0.21 -0.17 0.02

Agreeableness .63*** .53*** .58*** .75***

Conscientiousness 0.1 0.16 0.1 .34**

*p<0.1 **p<0.01 ***p<0.001Table 5: GPI™ Agreeableness sub domains and the scales of MBTI and NEO

Implementation Conscientiousness Achievement

MBTI Introversion 0.02 0.14 0.15

Extraversion -0.14 -0.11 -0.1

Sensing .45*** 0.22 -5

Intuitive -�53*** -.24* 0.04

Feeling .23* 0.15 0.12

Thinking -.26* -0.17 0.02

Judging .58*** .42** .31*

Perceiving -.60*** -.41** -.23*

NEO Neuroticism 0.12 -0.05 0.01

Extraversion -0.05 -0.03 0.16

Openness -.33* 0.03 .25*

Agreeableness .30* .51*** 0.21

Conscientiousness .47*** .63*** .47***

*p<0.1 **p<0.01 ***p<0.001



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internal correlation

Method

125 people taken from the general UK population participated in the study. All subjects were English-speaking volunteers, with an even gender distribution and age ranging from 16 to over 60 (table 7 and 8).

Gender % Age Group %

Male 51 < 21 8

Female 49 21-30 25

31-40 8

41-50 34

> 50 24

Tables 7 & 8: Details for the population sample

Results

Emotionality Extraversion Cognition Agreeableness Attainment

Emotionality 1

Extraversion .25* 1

Cognition -0.12 .51*** 1

Agreeableness -.30* -.24* -0.12 1

Attainment 0.05 -.19* -.41** .35** 1

*p<0.1 **p<0.01 ***p<0.001Table 9: Correlations of GPI™ domains

Anxiety Hostility Optimism Self-Esteem Impulsive Emotionality

Anxiety 1

Hostility .42** 1

Optimism .46*** .36** 1

Self-Esteem .62*** .48*** .38** 1

Impulsive -0.03 .46*** -0.1 0.17 1

Emotionality .76*** .78*** .64*** .78*** .42** 1

*p<0.1 **p<0.01 ***p<0.001Table 10: Correlations of GPI™ Emotionality sub domains

Sociable Assertiveness Hedonism Social Poise Extraversion

Sociable 1

Assertiveness 0.12 1

Hedonism .37** -.23* 1

Social Poise .48*** .54*** 0.04 1

Extraversion .71*** .62*** .40** .829*** 1

*p<0.1 **p<0.01 ***p<0.001Table 11: Correlations of GPI™ Extraversion sub domains


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Change Orientation Information Processing Decision Making Cognition

Change Orientation 1

Information Processing .75*** 1

Decision Making .26* .32* 1

Cognition .89*** .86*** .62*** 1

*p<0.1 **p<0.01 ***p<0.001Table 12: Correlations of GPI™ Cognition sub domains

Affiliation Trust Conformity Modesty Agreeableness

Affiliation 1

Trust .47*** 1

Conformity .68*** .41** 1

Modesty .32* .47*** .46*** 1

Agreeableness .79*** .77*** .83*** .72*** 1

*p<0.1 **p<0.01 ***p<0.001Table 13: Correlations of GPI™ Agreeableness sub domains

Implementation Conscientiousness Achievement Attainment

Implementation 1

Conscientiousness .48*** 1

Achievement .32* .58*** 1

Attainment .74*** .86*** .80*** 1

*p<0.1 **p<0.01 ***p<0.001Table 14: Correlations of GPI™ Attainment sub domains

Notes

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internal Reliability

Method

Data of 2312 individuals was included in the analysis. Of these, 1283 were male, 766 were female and 263 were unknown. Cronbach’s alpha was used to measure the internal reliability of the domains.

Gender %

Male 56

Female 33

Unknown 11

Table 15: Gender distribution in study population

Results and Discussion

Tables 16 to 20 show the Cronbach’s Alpha coefficients for the domains and sub domains making up the GPI™.

Domain and DimensionsCronbach’s Alpha

Coefficient

EMOTIONALITY 0.88

Anxiety 0.71

Hostility 0.71

Optimism 0.83

Self-Esteem 0.75

IMPULSIVE 0.77

Table 16: Emotionality


Coefficient

EXTRAVERSION 0.81

Sociable 0.69

Assertiveness 0.74

Hedonism 0.64

Social Poise 0.85

Table 17: Extraversion


Coefficient

COGNITION 0.83

Change Orientation 0.78

Information Processing 0.62

Decision Making 0.67

Table 18: Cognition


Coefficient

AGREEABLENESS 0.8

Affiliation 0.62

Trust 0.83

Conformity 0.63

Modesty 0.65

Table 19: Agreeableness


Coefficient

ATTAINMENT 0.82

Implementation Style 0.64

Conscientiousness 0.74

Achievement 0.59

Table 20: Attainment

A review by Charter (2003) of reliability coefficients sets the attained internal reliability coefficients in context. 2,733 test critiques, journal articles and test manuals published between 1927 and 2001 were included in the analysis. The average alpha coefficient for Personality tests was .77 which the GPI™ comes up favorably against. All of the Domains possess alpha levels above the average calculated by Charter (2003), as do many of their associated dimensions.


14 Technical Manual

Test-Retest Reliability

Method

57 people who had not completed the GPI™ before participated in the study. Under test conditions, individuals

Domain and Dimensions

Pearson’s r Correlation Coefficient Time 1 v Time 2

EMOTIONALITY 0.807**

Anxiety 0.78**

Hostility 0.70**

Optimism 0.73**

Self-Esteem 0.77**

IMPULSIVE 0.80**

Table 21: Emotionality



EXTRAVERSION 0.835**

Sociable 0.55**

Assertiveness 0.82**

Hedonism 0.78**

Social Poise 0.81**

Table 22: Extraversion



COGNITION 0.64**

Change Orientation 0.71**

Information Processing 0.39**

Decision Making 0.62**

Table 23: Cognition



AGREEABLENESS 0.80**

Affiliation 0.68**

Trust 0.65**

Conformity 0.62**

Modesty 0.78**

Table 24: Agreeableness



ATTAINMENT 0.75**

Implementation Style 0.83**

Conscientiousness 0.54**

Achievement 0.68**

Table 25: Attainment

Results

Tables 21 to 25 show the correlation coefficients for the domains and dimensions making up the GPI™ (** denotes significance level p<0.01).

completed the indicator twice with a time period of two weeks in between tests. The second testing session took place in the same room as the first session, at exactly the same time of day. Feedback was not given to the participants until after the second testing session.



15References

References

Barrick, M. & Mount, M. (1991). The “Big 5” personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44, 1-25

Charter, R.A. (2003) A breakdown of reliability coefficients by test type and reliability method, and the clinical implications of low reliability. The Journal of General Psychology.

Costa, P. T., Jr., & McCrae, R. R. (1985). The NEO Personality Inventory. Odessa, FL: Psychology Assessment Resources.

Fiske, D.W. (1949). Consistency of the factorial structures of personality ratings from different sources. Journal of Abnormal and Social Psychology, 44, 329 – 344

Guion, R.M. & Gottier, R.F. (1965). Validity of Personality Measures in Personnel Selection. Personnel Psychology, 18, 135-164

Hogan, J. & Holland, B. (2003). Using theory to evaluate personality and job-performance relations. Journal of Applied Psychology, 88, 100-112

McCrae, R.R. & Costa, P.T. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52, 81-90

Tett, R., Jackson, D. & Rothstein, M. (1991). Personality measures as predictors of job performance: A meta-analytic review. Personnel Psychology, 44, 703-725

Thurstone, L.L. (1934). The Vectors of Mind. Psychological Review, 41, 1-32

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