Paul Lambe
School of Education and Lifelong Learning
St Luke’s Campus
Heavitree Road
University of Exeter
Exeter
p.j.lambe@exeter.ac.uk
Conceptualising and measuring agency using the British
Household Panel Survey
A paper presented at the BERA Annual Conference 6-9
September 2006, University of Warwick,
This working paper was produced as part of the Learning Lives Project*.
Copyright lies with the author. If you cite or quote, please be sensitive to the fact
that this is work in progress
*The Learning Lives: Learning, Identity and Agency project (see
learninglives.org) is a collaboration between the Universities of Exeter, Brighton,
Leeds and Stirling and is funded by the Economic and Social Research Council
as part of their Teaching and Learning Research Programme (TLRP) see
www.tlrp.org
Conceptualising and measuring agency using the British Household Panel
Survey
Introduction
The concept of agency is of central concern to the Learning Lives project. The project
aims to understand the relationship between adult learning and agency over the life
course in terms of how learning impacts on agency and, conversely, how agency
impacts on learning. The project approaches learning as one of the ways in which
people respond to events in their lives, often to gain more control over their lives. To
further these aims it is necessary to critically evaluate whether empirical evidence
supports or disputes theoretical connections between agency and adult learning.
However, as outlined below, agency is a rather broad and elusive latent concept. This
paper takes a preliminary step in this direction as its purpose is to characterise one
major aspect of the self’s agency, self-efficacy, using items (questions) from the
British Household Panel Study1 (BHPS). Furthermore, this paper illustrates the
application of Latent Class Analysis, a powerful new tool in the analysis of typologies
and scale response patterns from categorically scored survey data using the LEM
2
software programme.
Theorisation of Agency
In recent years much valuable theoretical writing has appeared that has increased our
understanding of agency (Yoder 2000, see Cote and Levine 2002 for a review of the
psychological and sociological literature, see Emirbayer and Mische 1998 for a
review of literature theorising agency). Nevertheless, the concept of agency, as the
following brief review of literature points up, has maintained an ‘elusive…
vagueness’ (Emirbayer and Mische 1998:962). Karen Evans, has identified 12 factors
of importance in the analysis of ‘bounded’ agency and control :- sociability,
confidence, fulfilled work life and fulfilled personal life, belief that opportunities are
open to all, belief that own weaknesses matter, belief in planning not chance, belief
that ability not rewarded, active career seeking, unlikely to move, politically active,
helping/people career oriented, and negative view of future (Evans 2002:255). John
1
The British Household Panel Survey (BHPS), started in 1991, is conducted by the ESRC UK Longitudinal Studies Centre
together with the Institute for Social and Economic Research at the University of Essex. The BHPS was designed as an annual
survey of each adult (16+) member of a nationally representative sample of more than 5,000 households, making a total of
approximately 10,000 individual interviews. The same individuals are re-interviewed in successive waves and, if they split off
from original households, all adult members of their new household s are also interviewed. Children are interviewed once they
reach the age of 16; there is also a special survey of 11-15 year old household members from wave 4 onwards (1994). Thus the
sample should remain broadly representative of the population of Britain as it changed through the 1990s and beyond. At wave 9
(2000) two additional samples to the BHPS in Scotland and Wales were added thus permitting independent analyses of these
countries and comparative analysis with England. At wave 11 (2002) an additional sample from Northern Ireland was added to
increase the representivity of the whole of the United Kingdom. Documentation and questionnaires available at
www.iser.essex.ac.uk/ulsc/bhps
2
LEM : A general programme for the analysis of categorical data, (log linear and event history analysis
with missing data using the EM algorithm. See http>//spitswww.uvt.nl/~vermunt
1
Bynner sees personal agency as comprised of an individual’s disposition (sense of
self-efficacy, sense of internal locus of control, motivation, aspiration and selfesteem) and resources (social, cultural, human capital), including community
resources and an individual’s membership of, and activity in community/civic
organisations which may enhance an individual’s social and human capital and
improve that individual’s prospects and indeed, sense of agency (Bynner 2001:23).
Yaojun Li, Andrew Pickles and Mike Savage, using BHPS data, have taken a more
nuanced view and have broken down the concept of social capital into three distinct
dimensions; ‘civic participation, social networks and neighbourhood attachments’,
and argue that ‘civic participation is just one out of a range of channels of social
capital generation’ and that more ‘informal networks affect people’s attitudes, values,
preferences and key aspects of their life-chances’ (Li et al 2003:16). Emirbayer and
Mishe comment that the concept of agency has been associated with, inter alia,
motivation, will, sense of purpose, intentionality, choice, initiative, and goal seeking
(Emirbayer and Mische 1998). Whilst Cote and Levine’s construct, identity capital,
cites agency residing in and emanating from tangible personal assets such as
memberships of organisations, and intangible personal assets such as internal locus of
control, self-esteem, self-efficacy, a sense of purpose in life, the ability to selfactualise and ideological commitment which ‘combine to predict identity capital in
terms of formulating a stronger sense of adult identity’ (Cote and Levine 2002:143149).
Gert Biesta and Mike Tedder have conceptualised agency not as an ‘individual
possession but something that is achieved in action’ which they argue calls for ‘an
ecological understanding of agency’ (Biesta and Tedder 2006). Like Emirbayer and
Mishe, they contend that individuals, influenced by past achievements,
understandings and patterns of action, who are motivated to realise a future that is
different from their past, can only act out this intention in the present, or plan for the
future. Thus in a context in which each individual’s capacity to make ‘practical and
normative judgements among alternative possible trajectories of action [is conditioned
by the] emerging demands, dilemmas and ambiguities of presently evolving
situations’(Emirbayer and Mishe 1998, quoted by Biesta and Tedder 2006). Their
emphasis on changing contexts-for-action over time raises fundamental questions
about the relationship between agency and learning in the life course. Not least : why
individual’s can be agentic in one situation and not another, why an individual’s
capacity for agentic behaviour can change over the life course, and what are the
catalysts that initiate the learning processes which enable people to reconstruct their
agentic orientations. At the same time Biesta and Tedder emphasise that ‘agentic
orientations … are never sufficient to understand actual agency … because [direction
of one’s life] … also depends on contextual and “ecological” factors and on available
resources within a particular ecology’( ibid: p9).
One of the principal tenets of life course theory is the significance of human agency in
life course construction and at the core of human agency is the self, or self-agency
(Elder, 1974, 1995, Gecas 2004:369, Badura 1997:3). Self-agency underpins
Bandura’s theory of self-efficacy, indeed ‘efficacy belief [is regarded as]… a major
basis of action’ and Bandura defines perceived self-efficacy as ‘not a measure of the
skills one has but a belief about what one can do under different sets of conditions
with whatever skills one possesses’ (Bandura 1997:37). Gecas defines self-efficacy as
referring to the ‘perception of oneself as a causal agent in one’s environment, as
2
having some control over one’s circumstances , and being capable of carrying out
actions to produce intended effects’ (Gecas 2004, 370). There is much evidence of the
relationship between an individual’s self-efficacy and their functioning and wellbeing in the domains of academic achievement, occupational achievement, and
general physical and mental well-being (see Bandura 1997, Swartzer and Fuchs 1996,
). Indeed, Gecas argues that those with ‘high self-efficacy, especially in such domains
as education, inter-personal relations, and occupational contexts, are more likely to be
the architects of their own lives and to see themselves as such’, and that the converse
is more likely for those with low self-efficacy (Gecas 2004:370). Furthermore, in
relation to adult learning recent studies suggest that participation in adult learning has
a positive effect upon self-efficacy (Schuller et al 2002, Hammond and Feinstein
2005).Clearly, self-efficacy, an individual’s belief in his or her own efficacy and
personal control, is an important facet of the latent concept agency and major
influence upon life course construction.
This brief review of the theorisation of agency points up that it is crucial to locate
learning and agency in a temporal framework in order to examine their dynamic
qualities and the changing influences upon them. Furthermore, that the
characterisation of a measure of self-efficacy in isolation from contextual effects
emanating from various sources including those of social capital generation will allow
us to control for and test hypotheses concerning the effects upon this key element of
agency of changing contextual influences, thereby moving us towards an ecological
understanding of agency. This necessitates longitudinal analysis of panel data such as
the BHPS. However our immediate concern is an analysis using items from a single
wave of the BHPS to characterise the latent concept self-efficacy and examine its
relationship with adult learning.
Methodology
Much of previous research into agency, has employed factor analysis of survey items
to reduce many observed variables to only a few latent factors, and respondents’
predicted factor scores then used in post hoc analysis of the relationship between
agency and learning ( Evans 2002, Cote 1997, Li et al 2003, Hammond and Feinstein
2005). It is the case that the vast majority of variables in the most widely used social
science data sets, including the BHPS are scored as categorical data, either nominal or
ordinal. Clearly, when possible, it is preferable to select analytic techniques that
conform to the requirements of both the theoretical concept of interest and the nature
of the measures of the data available. For these reasons Latent Class Analysis (LCA)
is used here. LCA is a statistical method for studying categorically scored variables
that does not require data to meet the assumptions of multivariate normality and
continuity of measurement, and is eminently suited for life course analysis using
categorically scored survey data. It provides a powerful new tool in the analysis of
typologies (classes), either as a method for empirically characterising a set of latent
types within a set of observed indicators or as a method for testing whether a
theoretically posited typology adequately represents the data. LCA can be considered
as a ‘qualitative data analogue to factor analysis. It enables researchers to empirically
identify discrete latent variables [ e.g agency, religious commitment] from two or
more discrete [categorical] observed variables’ ( McCutcheon 1987:7, McCutcheon
and Mills 1998, Vermunt, 1997a). Indeed recent developments allow analysts to
include variables of mixed type (nominal, ordinal, continuous/and or count variables)
3
in the same analysis. LCA is a flexible methodology that enables researchers: to
identify a set of mutually exclusive latent classes, or typologies, from observed
categorically scored survey data, and thus empirically characterise typological
classifications (multidimensional). It also enables researchers to analyse the
scalability of a set of observed categorical items into ordinal measures of a latent
variable, and additionally allows us to discern whether the defined latent variable
( e.g. self-efficacy) is invariant over multiple populations (i.e. comparative analysis of
scale characteristics and typologies in different populations, social groups.
Furthermore, models for the analysis of categorically scored panel data allow us to
examine and test formal hypotheses about the nature of change in scale characteristics
and typologies identified using identical measures at different times for the same
population (passim McCut cheon 1987, see also McCutcheon 1996, Macmillan and
Eliason 2004, Vermunt 1997b). Hence, the appropriateness of LCA for examining
the relationship between adult learning and self-efficacy over the life course using
panel data such as the BHPS.
At BHPS wave 11 (2001) a block of items, CASP-19 (a 19 item Likert scaled index
measuring quality of life), was included as a core rotating component ( CASP-19 will
be included again at wave 16). CASP-19 was originally developed as a measure of
quality of life in early older age and specifically designed to exclude ‘contextual and
individual phenomena that might influence it, such as health, social networks, and
material circumstances’ and specifically designed to tap into the agency of older
people (Hyde et al 2003:187). The CASP19 scale has been used in the English
Longitudinal Study of Ageing, the UK Whitehall Study, the US Health and
Retirement Study and a shorter version in the Study of Health, Ageing and Retirement
in Europe. A raft of studies have validated this measure3, and its development is
outlined in Hyde et al 20034. However the BHPS is the first survey to use the scale
on its whole sample of respondents at all ages because of its proven reliability and
validity. The items in the CASP-19 scale (see Table 1 below) tap four domains:
control, autonomy, self realisation and pleasure. Clearly, as intended by its authors, in
the three domains of control, autonomy and self-realisation the items tap in to sense of
agency and self-efficacy as theorised by Bandura , and empirically evidenced by
Evans, Bynner, Cote and Levine, Emirbayer and Mische. The inclusion of CASP-19
in the BHPS as a core rotating component will no doubt prove to be an extremely
useful resource in longitudinal educational research as an instrument to measure sense
of agency and its relationship with learning over time, albeit an instrument whose
data collection points are at five yearly intervals.
However, what is required for our purposes is an equivalent instrument whose data
are recorded in the smallest possible units of time, and in the case of the BHPS this
would be at each annual wave. Fortunately, at all waves of the BHPS since 1991
onwards a General Health Questionnaire has been included, and along with other
BHPS core questions we are able to construct an instrument whose items approximate
those used in the domains of control, autonomy and self-realisation of CASP-19.
Table 2 below outlines these core BHPS items and their counterparts in CASP-19.
3
See www1.imperial.ac.uk/medicine/people/d.blane for an extensive list of publications by Professor David Blane, Department
of Medecine, Imperial College.
4
See Hyde, M., Wiggins, R.D., Higgs, P., and Blane, D., (2003) A measure of quality of life in early old age : the theory
development and properties of a needs satisfaction model (CASP-19), pp 186-194 in Aging and Mental Health, 7, (3).
4
Table 1:Item wording and domains for CASP-19 Each item has the response categories coded as
follows, Often =3, Not Often=2, Sometimes =1, and Never=0.
CONTROL
AUTONOMY
PLEASURE
SELFREALISATION
My age prevents me from doing the
things I would like to
I feel that what happens to me is out of
my control
I feel free to plan for the future
I feel left out of things
I can do the things that I want to do
Family responsibilities prevent me from
doing what I want to do
I feel that I can please myself what I can
do
My health stops me from doing the things
I want to do
Shortage of money stops me from doing
the things I want to do
I look forward to each day
I feel that my life has meaning
I enjoy the things that I do
I enjoy being in the company of others
On balance I look back on my life with a
sense of happiness
I feel full of energy these days
I choose to do things I have never done
before
I feel satisfied with the way my life has
turned out
I feel that life is full of opportunities
I feel that the future looks good for me
5
Table 2: BHPS proxy items and their CASP-19 counterparts ( excludes item 1 My age prevents
me from doing the things I would like to). The emboldened items in the CASP-19 column form
the eight item version. The BHPS items which appear at all waves, KGHQC-L, KHLLT( *** this
item does not appear at waves I and n of the BHPS, however values at preceding and consecutive
waves allow imputation of missing values), KFISITX, reverse coded where necessary and
dichotomised.
BHPS items all waves
Have you recently been able to face
up to problems ?
(Item KGHQF)
Domain
CASP-19 items
I feel that what happens to me is
out of my control *
CONTROL
I feel free to plan for the future
I feel left out of things*
( Item KQLFD)
Have you recently felt you are
playing a useful part in things?
( Item KGHQC)
I can do the things that I want to
do *
Have you recently been losing
confidence?
(Item KGHQJ)
AUTONOMY
Family responsibilities prevent me
from doing what I want to do
I feel that I can please myself
what I can do*
*************************
Have you recently felt capable of
making decisions about things?
(Item KGHQD)
Does your health in any way limit
your daily activities compared to
most people of your age?
( Item KHLLT)***
My health stops me from doing
the things I want to do*
How well would you say you were
managing financially?
(Item KFISIT)
Have you recently been able to
enjoy your normal day to day
activities
(Item KGHQG)
Have you recently felt constantly
under strain?
(Item KGHQE)
***********************
Shortage of money stops me from
doing the things I want to do
Have you recently been feeling
reasonably happy all things
considered?
(Item KGHQL)
Have you recently been thinking of
yourself as a worthless person?
(Item KGHQK)
Looking ahead how do you think
you will be financially a
year from now?
(Item KFISITX)
I look forward to each day
I feel full of energy these days
SELF-REALISATION
I choose to do things I have never
done before
I feel satisfied with the way my
life has turned out*
I feel that life is full of
opportunities*
I feel that the future looks good for
me*
Analysis: Part 1
6
Our sample comprised 5,718 adults of working age (BHPS wave 11, England only)
females aged 16-59 years and males aged 16-64. Firstly, all CASP-19 items in the
domains of CONTROL, AUTONOMY and SELF REALISATION were subject to
LCA and a more parsimonious seven-item shorter version derived (see Table 2, the
emboldened items in the CASP-19 column, recoded 1 for a non -agentic response and
2 for an agentic response) . Latent class analysis of the seven-item CASP scale
produced a two class model which assigned cases into two distinct typologies. Class 1
in which there was a very high probability of an agentic response to each of the seven
items and class two in which respondents had very low probability of an agentic
response to each item. Table 3 below outlines the conditional probabilities of an
agentic response to the items in the scale and the Latent Class probabilities, that is, the
probability of a respondent belonging in either the agentic or non-agentic group given
their responses to the shortened seven-item CASP instrument. Eighty percent of
respondents were classified as agentic. Thus 8 in 10 of our sample are typified as
having a positive perception of their self-efficacy, and two in ten of the sample as
having a much poorer perception of their self-efficacy. Clearly, as the CASP-19 was
designed specifically to tap into sense of agency and is a much validated instrument in
its entirety and in its shortened versions, these findings come as no surprise
Nevertheless, the analysis confirms that our seven- item version is a valid measure of
self-efficacy.
The next step in the analysis was to examine the relationship between the seven-item
version of CASP-19 and variables shown to have an effect on the likelihood of low
self-efficacy and thereby test its external validity. Respondent’s employment status
was added to the above model as a grouping variable and the null- hypothesis tested
that it would have no effect upon the probability of a respondent being assigned to
either of our two latent classes of self-efficacy. The conditional probability of an
unemployed respondent being assigned to the non-agentic latent class,(ie. those with
a poor perception of self-efficacy) was .8759, and the conditional probability of being
unemployed and being assigned to the agentic latent class a mere 0.1241. Thus the
null- hypothesis was rejected, and evidence shown that the relationship between our
grouping variable, employment status and each of our indicator variables ( items in
the instrument) are mediated through the latent concept self-efficacy. Clearly, being
unemployed has a significant impact upon self-efficacy. Similarly a grouping
variable, academic qualifications was added to the model (no qualifications or
CSE=1, O-level or above=2) and the null- hypothesis tested that it would have no
effect upon the probability of a respondent being assigned to either of our two latent
classes of self-efficacy. The analysis revealed a conditional probability of .7898 of a
respondent being in the agentic latent class for those with O-level or above academic
qualifications, and a conditional probability of .2202 of being in the agentic class
given a respondent had no qualifications or CSEs. Thus, the null- hypothesis was
rejected, and evidence shown that the relationship between our grouping variable,
academic qualification, and each of our indicator variables (items in the instrument)
are mediated through the latent concept self-efficacy.
So far in this paper it has been shown that LCA has great potential to unravel the
associations between learning and self-efficacy. However, what is needed is an
equivalent instrument to the seven-item CASP scale, one that is comprised of items
which appear at each wave of the BHPS and which can be shown to be measuring the
same underlying latent concept. Such an instrument would enable the relationships
between learning and self-efficacy to be examined over time and the full potential of
7
the BHPS to be mined. It is this task that the next part of the analysis turns its
attention.
Table 3: Probability of an agentic response expressing self-efficacy and the Latent Class
Probabilities for the two-class model, (n=5,718).
Observed
Respondent Type
CASP -Variables
A
B
C
D
E
F
G
Relative Class Frequency
Agentic
.7893
.7983
.9412
.8416
.8517
.9813
.9427
Non-agentic
.2107
.2017
.0588
.1584
.1483
.0187
.0573
.8019
.1981
Analysis: Part 2
The aim of the analyses presented in this section is to create an instrument to measure
self-efficacy using the proxy items that appear at all waves of the BHPS (emboldened
items in first column of Table 2) and evidence that these items are measuring the
same underlying concept as their counterparts in the seven- item scale derived from
the validated CASP-19 measure of sense of agency. To do this, individually each of
the proxy items is added to the seven-class CASP model and an equality restriction is
imposed on the conditional probabilities. In this way a parallel indicators hypothesis
can be tested by imposing a restriction on the model that the proxy item is a parallel
indicator of its counterpart in the seven- item CASP scale, i.e. that they are both
measuring the same thing and that the conditional probability of a respondent being
assigned to class 1 or class2 of our latent concept self-agency in response to either
indicator, at either level of each indicator, agentic or non-agentic, is the same. When
testing a parallel indicator hypothesis what we are saying is that two of our indicator
variables in the model have identical error rates with respect to each of the latent
classes of self-efficacy.
This can best be illuminated by an equation: where π is the conditional probability, B
is an indicator from the seven-item CASP derived instrument and B1 and B2 its two
categories, non-agentic and agentic responses respectively, C is a proxy item from the
BHPS which appears at all waves and C1 and C2 are respectively the non-agentic and
agentic responses, X 1 is the non-agentic level (class 1) of the latent concept selfefficacy, X2 is the agentic level (class 2) of the latent concept self-efficacy,
π B1\X1
=
π C1\X1
and
π B2\X2
=
π C2\X2
For example we hypothesised that proxy BHPS item KGHQC (Have you recently felt
you are playing a useful part in things?) is a parallel indicator of KQLFC (I feel left
8
out of things). Parallel hypothesis tests were carried out for all the proxy items and
their corresponding items from the validated seven-item CASP scale. Two goodness
of fit statistics allow us to evaluate the nearness of our models to the actual observed
data., the Pearson Chi square and the Likelihood ratio chi square. When using the
seven- item CASP scale with the addition of a proxy indicator as a base model, the
restricted model imposing the hypothesis of parallel indicators becomes a nested
model and thus we can use the conditional likelihood ratio X- square test to examine
whether the newly imposed restriction is acceptable, or whether the restriction results
in an unacceptable erosion of fit to the observed data. In all cases we were able to
accept our proxy items as parallel indicators of the seven- items derived from analysis
of the CASP-19 scale, albeit with some erosion of fit between the models and the
observed data. Thus in the next section we are able to test our new seven- item selfefficacy scale to see if latent class analysis results in respondents being assigned with
an acceptable level of probability to two distinct levels of the latent concept selfefficacy.
Analysis: Part 3
In this section the results of a latent class analysis of the proxy indicators of our latent
concept self-efficacy are presented. The items in scale are, KGHQF, KGHQC,
KGHQJ, KGHQD, KHLLT, KGHQL, and KGHQK (the questions asked are outlined
in the first column of Table 2 above). Latent class analysis of the proxy items scale
produced a two class model which assigned cases into two distinct typologies. Class
1, in which there was a very high probability of an agentic response to the sevenproxy items and class two in which respondents had very low probability of an
agentic response to each item . Table 4 below outlines the conditional probabilities of
an agentic response to the items in the scale, and also the Latent Class probabilities
i.e. the probability of a respondent belonging in either the agentic or non-agentic
group given their responses to the shortened seven-item proxy instrument. Some
85% of respondents in the sample were classified as agentic and 15% as having a
poorer perception of their self-efficacy. These findings are very much in line with
those of the seven- item shortened version of the validated CASP-19 instrument.
Table: 4: Probability of an agentic response expressing self-efficacy and the Latent Class
Probabilities for the two-class model using BHPS proxy items (n=5,718).
Observed
KGHQF
KGHQC
KGHQJ
KGHQD
KHLLT
KGHQL
KGHQK
Relative Class Frequency
Respondent Type
Agentic
.9422
.9684
.9696
.9840
.9091
.9476
.9964
.8526
Non-agentic
.0578
.0316
.0304
.0160
.0909
.0524
.0036
.1474
Analysis: Part 4
9
Clearly the seven-item scale derived from proxy indicators included in the BHPS at
all waves is measuring the same underlying latent concept as the validated CASP
scale, i.e. self-efficacy. Nevertheless it is still necessary to test this new seven-item
instrument for external validity. To do this a representative sample of 1393 English
respondents aged 20 to 30 years old respondents from wave 11 of the BHPS was
analysed using their responses to seven-item scale and including the two indicators
employment status and academic qualifications.
The results of this analysis clearly evidence that the new seven item instrument
assigns respondents in the sample to two definite classes, or typologies of selfefficacy, and that once again employment status and academic qualification are
significant indicators in the probability of being assigned to the agentic class of
respondents with a positive sense of agency or self-efficacy or to the class of
respondents with a poorer perception of their self-efficacy. Table:5 below outlines the
LCA two-class model of self-efficacy i.e. the conditional probabilities of an agentic
response to the items in the scale, and also the Latent Class probabilities. In this
sample of 20 to 30 year olds almost 86% of respondents were assigned to the agentic
class with a positive perception of their self-efficacy and 14% to the class with a
poorer perception of their self-efficacy. Once again those respondents who are
employed and with academic qualifications from O-level or above have a much
greater likelihood of being in the agentic class, and conversely those who are
unemployed or have no academic qualifications/CSE have a very small likelihood of
belonging tothe agentic group with a positive self perception of sense of agency.
Table 5: Probability of an agentic response expressing self-efficacy and the Latent Class
Probabilities for the two-class model using BHPS proxy items and a sample of 20 to 30 year olds
derived from wave 11 of the BHPS (n=1393).
Observed
Respondent Type
Agentic
Non-agentic
KGHQF
.9406
.0594
KGHQC
.9645
.0355
KGHQJ
.9585
.0415
KGHQD
.9844
.0156
KHLLT
.9607
.0393
KGHQL
.9583
.0417
KGHQK
.9944
.0056
EMPLOYED
.8444
.1556
QUALIFICATION
.8250
.1750
Relative Class Frequency
0.8597
0.1403
Conclusions
The analyses set out in this paper aimed to develop a measure of self-efficacy using
data from a panel study in order that the relationship between learning and this major
aspect of agency could be measured over time in changing contexts. Firstly, the
CASP-19 instrument which appeared at wave 11 of the BHPS, and which was
specifically designed to measure sense of agency was reduced to a shorter version.
This new instrument was shown to be an equally good measure of self-efficacy as the
original instrument it was derived from. Proxy items corresponding to those in the
10
reduced CASP instrument and which appear at all waves of the BHPS were
evidenced to be an effective instrument for measuring self-efficacy.
The methodological contribution of this paper is two-fold. Firstly, in the provision of
an instrument that will enable researchers to measure self-efficacy over time and
thereby disentangle the effects of changing contexts on people’s perceptions of their
self-efficacy. Secondly, in illustrating the use of a modern statistical approach to the
analysis of categorically scored survey data, which is eminently suited to analysing
panel adapt and change over time.
The substantive findings of this paper evidence that employment status and academic
qualification are important influences upon a person’s sense of agency and these
findings point to the importance of adult learning. However, the use of this new
instrument will enable researchers to examine the relationships between adult
participation in education and training and self-efficacy over the life course using the
British Household Panel Survey. The LEM output from all the above analyses and
outline of the models evaluation criteria is available on request to the author.
The links between adult learners’ capacity to act autonomously, learning and the
effects of changing structural contexts over time are complex, a complexity
compounded and confounded by disparate experiences, of transitions in social roles,
of transitions in dispositions informed by the past and expectations for the future and
constrained or facilitated by the present. It is hoped that the methodological
contribution of this paper is its illustration of the flexibility and strengths of Latent
Class Analysis as tool to untangle this complexity.
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Appendix
1
See Fayers, Book review of Item Response Theory for Psychologists, by Embretson,
S.E. and Reise, S. pp 715-716 in Quality of Life Research 13, 2004. IRT advantages:
item selection, scale shortening using multi-item scales to evaluate latent concepts,
estimates probability of individual’s response to an item will lie in a particular
category. Disadvantages: specialist and not user-friendly software, poorly
documented, different software programmes produce different results same data,
difficult to use statistical goodness-of-fit methods to compare the various models
produced, little theoretical research re sample size effects, small number of outliers
disproportionately affect model fit.
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