Articles
Analyzing the Interviewers’ Evaluative Questions in Phone Polls
*
†
‡
Alyaa Roshdy Zahran , Aya R. Farag , Hesham M. Aly
Keywords: telephone polls, evaluative questions, biplot
DOI: 10.29115/SP-2012-0025
Survey Practice
Vol. 5, Issue 4, 2012
Analyzing the Interviewers’ Evaluative Questions in Phone Polls
introduction
Usually national surveys include some questions that are related to the
interviewer’s characteristics as well as interview evaluative questions to be
answered by the interviewer to reflect on the completed interview.
Considerable research has been devoted to study interviewer effects (age, race,
gender, experience, attitudes) (see Berk and Bernstein 1988; Groves and
Magilavy 1986; Groves et al. 2004; Hill 2002; Kish 1962; Singer et al. 1983;
Stokes and Yeh 1988). Few papers, however, studied the evaluation questions.
In the context of telephone polls, only two studies: The Gallup Organization
(1998) and Tarnai and Paxson (2005), studied the interviewer’s evaluative
questions. These questions could highlight the need of improvement in many
directions, like choosing target population, question wording, raising
awareness among specific groups in the society, etc.
Beginning in 2009, two questions were added to each poll at the Public
Opinion Poll Center (POPC) at the Information and Decision Support Center
(IDSC) of the Egyptian Cabinet. The first question identifies a “less than
good” interview (defined in terms of some identifiable problem) from the
perspective of the interviewer while the second question specifies what kind of
problem was encountered. Thirty-four polls of POPC during January 2009April 2010 are analyzed in this paper. The political and social polls suffer from
the existence of high percentages of interviews with problems. In most of our
polls, region is significantly associated to interview type, while in all the polls
gender is significantly associated with interview type. As respondent education
level increases, the interview tends to be good, whereas as the respondent gets
older, the interview tends to be a less than good interview. The most reported
problem is “not understanding the meaning of some questions.” A biplot
shows that the reported problems partition in four groups (clusters), where
*
†
‡
Institution: STAT Dept, FEPS-Cairo University
Institution: Poll Center, Information and Decision Support Center, Egyptian Cabinet
Institution: Poll Center, Information and Decision Support Center, Egyptian Cabinet
Analyzing the Interviewers’ Evaluative Questions in Phone Polls
group members are positively correlated together. There is no association
between poll type and the reported problems.
less than good interview and the reported problems
Figure 1 presents sample sizes and the proportions of interviews with problems
by poll type (political, social, media, and health). The proportions are high and
range from 0.075 to 0.259. On average, differences among these proportions by
poll type are not significant (Kruskal–Wallis p-value=0.648).
Figure 1
Proportion of interviews with problems and sample size in each poll grouped by type of the poll.
Thirteen reasons were reported for having a less than good interview. These
reasons were coded as a multiple response question. Table 1 presents the
percentages of each problem within each poll. The maximum percentage is
61.5 percent while the minimum value is 0. On average, one problem is
reported most often: “not understanding the meaning of some questions” with
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
a standard deviation of 0.15. This problem is also reported the most controlling
for poll type. Within each poll type, the problems are divided into three groups:
low (below 5 percent), medium (5–20 percent) and high (above 20 percent)
reported problems.
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
Table 1
Percentage of problems identified in the polls [weighted data].
Poll
Type
Health
Media
Political
Poll Name
Hearing
Knows
nothing
about
Topic
Noise
existence
Doubt
in
answers
Reluctant
Ironic
answers
Not
understanding
meaning of
some
questions
Not
interested
in surv
surve
ey
subject
Others
sharing
answers
Respo
ill
Rushed
Did
not
want
to be
called
again
Swine Flu_1
0.11
0.27
0.30
0.22
0.10
0.11
0.28
0.15
0.03
0.03
0.03
0.01
Swine Flu_2 -Oct09
0.06
0.09
0.23
0.30
0.11
0.08
0.54
0.09
0.11
0.01
0.07
0.01
Swine Flu_3_Nov09
0.05
0.03
0.26
0.20
0.19
0.05
0.60
0.05
0.12
0.01
0.04
0.02
Calculate it
correct_1
0.01
0.29
0.21
0.34
0.04
0.02
0.25
0.06
0.06
0.03
0.03
0.01
Calculate it
correct_2
0.02
0.45
0.19
0.22
0.07
0.04
0.22
0.24
0.12
0.03
0.02
0.00
Performance Pop
Media_09
0.18
0.21
0.24
0.22
0.22
0.14
0.54
0.26
0.18
0.00
0.05
0.02
Calculate it
correct_3_Jul09
0.04
0.57
0.10
0.35
0.05
0.02
0.15
0.16
0.02
0.01
0.05
0.00
Media
Performance_Repve
Health & Family
Planning
0.04
0.28
0.20
0.24
0.09
0.04
0.53
0.09
0.08
0.02
0.05
0.00
Calculate it
correct_4_Dec09
0.03
0.48
0.14
0.33
0.11
0.04
0.21
0.17
0.09
0.01
0.06
0.02
Television
0.05
0.15
0.24
0.35
0.29
0.11
0.28
0.20
0.28
0.01
0.11
0.02
Eval Gov’s
Decisions_09
0.07
0.30
0.23
0.20
0.09
0.05
0.19
0.17
0.12
0.04
0.05
0.00
The Gaza War
0.03
0.25
0.31
0.21
0.07
0.05
0.53
0.18
0.07
0.04
0.06
0.01
The Credibility of
the Gov
0.06
0.12
0.34
0.27
0.03
0.04
0.40
0.12
0.07
0.01
0.06
0.00
Eval Gov’s
Performance
0.03
0.17
0.25
0.32
0.08
0.09
0.27
0.13
0.19
0.03
0.06
0.00
Obama Visit_before
0.05
0.52
0.15
0.23
0.04
0.04
0.08
0.14
0.06
0.01
0.02
0.01
Obama Visit_after
0.06
0.43
0.23
0.18
0.06
0.07
0.20
0.25
0.06
0.01
0.03
0.01
Trends
States_October
0.05
0.30
0.25
0.25
0.15
0.05
0.10
0.18
0.17
0.01
0.07
0.01
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
Poll
Type
Social
Ironic
answers
Not
understanding
meaning of
some
questions
Not
interested
in surv
surve
ey
subject
Others
sharing
answers
Respo
ill
Rushed
Did
not
want
to be
called
again
Poll Name
Hearing
Knows
nothing
about
Topic
Eval some Public
Services_before
match_Nov09
0.01
0.04
0.27
0.39
0.10
0.05
0.46
0.09
0.05
0.01
0.02
0.01
Eval some Public
Services_after the
match
0.08
0.14
0.27
0.31
0.19
0.05
0.50
0.10
0.11
0.04
0.05
0.02
Public Services/
Trends States_Jan
10
0.03
0.19
0.27
0.42
0.32
0.04
0.39
0.09
0.11
0.01
0.01
0.01
Public Services/
Trends
States_Jan10_2
0.05
0.08
0.30
0.34
0.31
0.00
0.41
0.09
0.16
0.00
0.01
0.00
Evaluation of the
Government’s
Decisions_Jan10
0.05
0.04
0.15
0.33
0.09
0.01
0.26
0.26
0.07
0.00
0.06
0.00
Mubarak Visit to
USA
0.02
0.40
0.21
0.18
0.06
0.03
0.14
0.16
0.02
0.01
0.04
0.01
Nazif in Beit
Beitk_Jul09
0.04
0.52
0.14
0.09
0.04
0.03
0.29
0.27
0.01
0.01
0.03
0.01
Traffic Pr in
Egypt_09
0.03
0.16
0.18
0.17
0.07
0.04
0.45
0.11
0.07
0.01
0.03
0.00
Renovating Religion
Speech
0.04
0.12
0.18
0.27
0.04
0.05
0.32
0.13
0.07
0.03
0.10
0.03
Women Role in
Society
0.03
0.03
0.20
0.26
0.08
0.08
0.53
0.01
0.07
0.00
0.05
0.01
E-Government
Services
0.06
0.54
0.19
0.16
0.03
0.06
0.30
0.11
0.06
0.00
0.02
0.02
Population Problem
0.04
0.16
0.29
0.13
0.13
0.02
0.49
0.09
0.10
0.03
0.03
0.01
What do the
Egyptians read?
0.02
0.03
0.41
0.17
0.03
0.05
0.14
0.07
0.18
0.01
0.10
0.02
Quality of Public
Transport09
0.09
0.10
0.26
0.32
0.14
0.13
0.29
0.06
0.07
0.01
0.11
0.06
The Traffic
0.06
0.07
0.29
0.47
0.16
0.04
0.50
0.10
0.02
0.05
0.06
0.00
Noise
existence
Doubt
in
answers
Reluctant
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
Poll
Type
Ironic
answers
Not
understanding
meaning of
some
questions
Not
interested
in surv
surve
ey
subject
Others
sharing
answers
Respo
ill
Rushed
Did
not
want
to be
called
again
0.02
0.03
0.13
0.02
0.01
0.02
0.05
0.01
0.21
0.14
0.05
0.46
0.20
0.07
0.02
0.06
0.01
0.23
0.26
0.11
0.05
0.34
0.13
0.09
0.02
0.05
0.01
0.07
0.09
0.08
0.03
0.15
0.07
0.06
0.01
0.03
0.01
Hearing
Knows
nothing
about
Topic
Noise
existence
Doubt
in
answers
Reluctant
Role of Public
Opinion
Polls_Sep09
0.05
0.62
0.12
0.26
Management
Corruption
0.04
0.28
0.20
Grand mean
0.05
0.25
Standard deviation
0.03
0.18
Poll Name
Problems in
Egypt_Feb10
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
biplot and its use in popc data set
While it is important to report the problem’s grand percentage, it is of more
interest to look at the underlying association structure (1) among the reported
problems,( 2) among the polls, or (3) between polls and reported problems.
The biplot of Gabriel (1971) helps in visualizing these structures. In a biplot,
a multivariate data set with n observations and m variables is represented with
n data-points and m axes. The length of the axis approximates the variable
variance. How data points are spread in the multi-dimension space (Euclidean
distances) reflects the association structure among these points; the closer the
points to each other the more association among them. The value of any
observation on any variable is measured by the product of axis length and
length of the perpendicular projection from the observation onto this axis.
Finally, the cosine of the angle between any two axes represents approximately
the correlation between the axes-variables (Kohler and Luniak 2005). The
biplot is offered in the well known statistical packages (SAS, R, and STATA)
and other specialized packages (e.g., GGEPlot and XLS-Biplots). However, we
used the Biplot add-in-Excel-macro of Lipkovich and Smith (2002) because it
is run on a user-friendly widespread platform.
For our weighted data set, the absolute measure of goodness of fit of the biplot
equals 71.6 percent. Although it does not exceed the 90 percent cutoff point
defined by Smith and Cornell (1993) for m>2, it slightly exceeds the 70 percent
cutoff point of Kohler and Luniak (2005), who emphasized that their cutoff
point suffices to approximate key features of the data. Figure 2 shows the biplot
of the 34-polls data. Two problems have the highest variability (longest axes):
“knowledge lack” and “not understanding the meaning of some questions”.
This information was also given in the last row of Table 1, however, it is easily
visualized in this plot. Four groups are formed:
• Group 1: Rushed, reluctant, not want to be called again, ironically
answering, noise existence, doubt in respondent answers, other
sharing answering the questions;
• Group 2: Not understanding the meaning of some questions,
hearing problems;
• Group 3: No interest in survey topic, knowledge lack;
• Group 4: Other problems, including illness.
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
Figure 2
Biplot of the 34 poll and the associated problems reported.
Group 4 members lay almost at the origin point. Members inside each group
are positively correlated together, in the sense that if one variable tends to
increase/decrease the other one will also tend to increase/decrease. In general,
as the angle between two variables is getting smaller the association increases.
Two variables at angles greater than 90 are negatively correlated, while an angle
of 90 reflects uncorrelated variables. Poll type does not play any role in the
spread of the polls (points) over the reported problems (axes). The points are
scattered randomly on all the axes without any pattern of clustering of any type.
Polls that cluster more around the axis of not understanding the meaning of
some questions should be revised specifically if it is going to be reused again.
respondent characteristics and interview type
The scatterplot is used to provide a quick summary for all association measures
and its p-value calculated from the 34 polls. To quantify the association
between interview type and gender or region, Cramer’s V is used. As this
statistic approaches one (zero), the association increases (diminishes). A
p-value which does not exceed the 5% significance level indicates a significant
association between the two variables. The upper left panel of Figure 3 depicts
the Cramer’s V-squared statistic vs. p-value scatterplot using gender and
interview type. There is a significant weak association between gender and
interview type (0.1<V-squared<0.4). The lower right panel of Figure 3 shows
Cramer’s V-squared statistic vs. p-value scatterplot using interview type and
region (urban governorates, lower governorates, upper governorates). The
association is very weak (~0.1) with most of these associations being significant.
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
Figure 3
Scatterplot of association measures between interview type and some respondent characteristics vs its p-value.
To quantify the association between interview type and education level (below
high school, high school or equivalent, university level or above) or age group
(18-less than 30, 30-less than 40, 40-less than 50, 50-less than 60, 60 and
above), the gamma measure is used. As the gamma value approaches 1 (zero)
in its absolute value, the association between the two variables approaches the
perfect association (independence) state. A negative (positive) gamma value
indicates that the two variables are negatively (positively) associated. The lower
left panel of Figure 3 shows the gamma-vs p-value scatterplot using interview
type and education level, while the upper right panel depicts the scatterplot
using interview type and age group. Significant negative association exists
between interview type and the education level, which ranges between -0.3 and
-0.7. Hence, as education level increases, there is a tendency that the interview
will be good. On the other hand, weak positive association exists between the
interview type and age group, except for five polls. Among those five polls, only
one has a relatively high gamma value (-0.138), and it is significant. For all the
other polls, as the respondent gets older, the interview tends to be less than
good. However, one should notice that not all the polls do have significant
association between interview type and age group.
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Analyzing the Interviewers’ Evaluative Questions in Phone Polls
conclusion
The interviewers rated large proportion of interviews in each poll as having
problems. On average, this proportion does not significantly differ by poll
type. In most of our polls, however, region is significantly associated to poll
type, while in all the polls, gender is significantly associated with poll type. As
respondent education level increases, the interview tends to be good, whereas
as the respondent gets older, the interview mostly tends to be less than good
interview. Raising awareness among elder or/and low educated ones would
help to decrease the probability of getting a less than good interview.
The reported problems of less than good interviews are divided into three
groups with regard to their occurrence percentage (low, medium, high). We
should work on the high and medium groups to eliminate/reduce their
occurrence. “Not understanding the meaning of some questions” is reported
the most on average in both grand average and within poll type average. It is
recommended to introduce an extra revision step in the process of writing the
questionnaire to ease the language and/or remove any ambiguous questions.
Good introduction could help in creating respondent-interest in the topic.
Questionnaires of periodic polls that do cluster more around the axis of not
understanding the meaning of some questions should be carefully revised.
According to the biplot, poll type does not affect the reported problems.
Regarding the correlation structure among the reported reasons, four groups
are distinguished from each other, where group members are positively
correlated together. A pair of groups are either independent from each other or
negatively correlated with each other depending on the angle between the two
groups.
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