Table of contents:
Sample Designs and Estimations
All surveys use nationally representative samples and include adults and children, male and female, rural and urban areas, referenced in specific regions, governorates and clusters. Statistical sampling methods were applied based on geographical division to design the sample of respondents. Respondent households belong to predetermined areas of the country. The number of households in each area is chosen to closely match the characteristics of the population at the national and subnational levels.
For the estimations in this publication, the weight applied to each area, household and individual, were considered. The weights usually state the number of units (individuals or households) represented in the population by each unit in the sample. Those sample weights are also useful for adjusting the proportion of each area (if the number of households in that area is over/under-sampled) and for adjusting for non-responses.
The diversity of the data sources and survey methodologies place three main limitations on this analysis: First, most surveys do not have a dedicated module on disability and simply ask one question regarding the disability status of the person (for example, “Do you suffer from a disability condition that is expected to last for more than six months?”). Second, even when surveys contain modules on disability, the questions vary and do not always conform to the WGSS methodology. Third, in some cases, it is not sound to provide disaggregated data on subsets of persons with disabilities (for example, children with disabilities under the age of five). Since persons with disabilities represent a small proportion of the total population, the repartition of this group into subgroups lowers the number of observations which can lead to a statistical bias.
Location /gender | Disability status | Total | Mean | Adjusted Wald test |
---|---|---|---|---|
Yemen (DHS 2013). Urban | With | 18 | 0.309025 | 0.7854 |
Without | 3,232 | 0.3396 | ||
Yemen (DHS 2013). Rural | With | 71 | 0.64235 | 0.075 |
Without | 10,793 | 0.514582 | ||
Yemen (DHS 2013). Male | With | 52 | 0.57158 | 0.3051 |
Without | 7,120 | 0.477069 | ||
Yemen (DHS 2013). Female | With | 37 | 0.526925 | 0.4733 |
Without | 6,905 | 0.455111 | ||
Egypt (DHS 2014). Urban | With | 28 | 0.210468 | 0.8171 |
Without | 5,575 | 0.232526 | ||
Egypt (DHS 2014) Rural | With | 31 | 0.208724 | 0.7899 |
Without | 8,295 | 0.229631 | ||
Egypt (DHS 2014). Male | With | 35 | 0.142217 | 0.1259 |
Without | 7,129 | 0.230593 | ||
Egypt (DHS 2014). Female | With | 24 | 0.318587 | 0.2803 |
Without | 6,741 | 0.200438 |
Location /gender | Disability status | Total | Mean | Adjusted Wald test |
---|---|---|---|---|
Yemen (DHS 2013). Urban | With | 5 | 0.141748 | 0.2488 |
Without | 1,265 | 0.437086 | ||
Yemen (DHS 2013). Rural | With | 18 | 0.37022 | 0.155 |
Without | 3,077 | 0.168519 | ||
Yemen (DHS 2013). Male | With | 13 | 0.312286 | 0.3329 |
Without | 2,221 | 0.171433 | ||
Yemen (DHS 2013). Female | With | 10 | 0.514049 | 0.0669 |
Without | 2,121 | 0.147028 | ||
Egypt (DHS 2014). Urban | With | 28 | 0.068624 | 0.7291 |
Without | 5,575 | 0.089923 | ||
Egypt (DHS 2014) Rural | With | 31 | 0.067188 | 0.7613 |
Without | 8,295 | 0.082666 | ||
Egypt (DHS 2014). Male | With | 35 | 0.06313 | 0.6257 |
Without | 7,129 | 0.084239 | ||
Egypt (DHS 2014). Female | With | 24 | 0.072965 | 0.8562 |
Without | 6,741 | 0.085608 |
Location /gender | Disability status | Total | Mean | Adjusted Wald test |
---|---|---|---|---|
Yemen (DHS 2013). Urban | With | 810 | 0.900595 | 0.0001 |
Without | 3,880 | 0.842624 | ||
Yemen (DHS 2013). Rural | With | 2,425 | 0.772149 | 0 |
Without | 10,209 | 0.84604 |
Note: With disability indicates the inclusion of at least one person with a disability in the household.
Location /gender | Disability status | Total | Mean | Adjusted Wald test |
---|---|---|---|---|
Jordan (HEIS 2013). Urban | With | 810 | 0.900595 | 0.0001 |
Without | 3,880 | 0.842624 | ||
Jordan (HEIS 2013). Rural | With | 2,425 | 0.772149 | 0 |
Without | 10,209 | 0.84604 | ||
Iraq (I-HSES 2012). Urban | With | 2,920 | 1344.024 | 0.0001 |
Without | 11,035 | 843.8889 | ||
Iraq (I-HSES 2012). Rural | With | 2,028 | 1202.882 | 0.007 |
Without | 7,286 | 751.6314 |
Note: With disability indicates the inclusion of at least one person with a disability in the household.
Location | Disability status | Total | Mean | Adjusted Wald test |
---|---|---|---|---|
Yemen (DHS 2013). Urban | With | 734 | 0.719027 | 0.0016 |
Without | 3,265 | 0.794407 | ||
Yemen (DHS 2013). Rural | With | 2,115 | 0.456726 | 0.0022 |
Without | 8,061 | 0.503938 | ||
Jordan (HEIS 2013). Urban | With | 221 | 0.590462 | 0.014 |
Without | 2,830 | 0.468809 | ||
Jordan (HEIS 2013). Rural | With | 115 | 0.673524 | 0.0573 |
Without | 1,684 | 0.550265 | ||
Iraq (I-HSES 2012). Urban | With | 2,991 | 0.988147 | 0.5795 |
Without | 11,893 | 0.986327 | ||
Iraq (I-HSES 2012). Rural | With | 2,129 | 0.767554 | 0.2838 |
Without | 8,133 | 0.750487 | ||
Egypt (HIECS 2015). Urban | With | 386 | 0.977632 | 0.6389 |
Without | 4,835 | 0.982774 | ||
Egypt (HIECS 2015). Rural | With | 533 | 0.91241 | 0.8244 |
Without | 6,234 | 0.915699 |
Note: With disability indicates the inclusion of at least one person with a disability in the household. Water is defined as improved if it comes from a household connection, a public standpipe, a borehole, a protected dug well or spring or from rainwater collection. Unimproved drinking water signifies water coming from an unprotected well or spring, from rivers or from ponds, as well as vendor-provided, bottled and tanker truck water. The data for Jordan pertains only to access to piped water, without taking into account other sources of improved water. See World Health Organization, undated.
Location | Disability status | Total | Mean | Adjusted Wald test |
---|---|---|---|---|
Yemen (DHS 2013). Urban | With | 733 | 0.983161 | 0.5162 |
Without | 3,265 | 0.986845 | ||
Yemen (DHS 2013). Rural | With | 2,111 | 0.641912 | 0.0091 |
Without | 8,052 | 0.681072 | ||
Jordan (HEIS 2013). Urban | With | 221 | 0.93678 | 0.6036 |
Without | 2,830 | 0.927857 | ||
Jordan (HEIS 2013). Rural | With | 115 | 0.860632 | 0.4135 |
Without | 1,684 | 0.899386 | ||
Iraq (I-HSES 212). Urban | With | 2,991 | 0.998952 | 0.825 |
Without | 11,893 | 0.998724 | ||
Iraq (I-HSES 212). Rural | With | 2,129 | 0.992918 | 0.9592 |
Without | 8,133 | 0.992766 | ||
Egypt (HIECS 2015). Urban | With | 386 | 0.990574 | 0.9916 |
Without | 4,835 | 0.990651 | ||
Egypt (HIECS 2015). Rural | With | 533 | 0.994306 | 0.9596 |
Without | 6,234 | 0.994149 |
Note: With disability indicates the inclusion of at least one person with a disability in the household. For Yemen, Iraq, and Egypt, access to electricity means access to publicly networked electricity. For Jordan, ownership of an electrical fan was used as a proxy for access to electricity.
[1] We use the Wald test to test differences in means across groups. The Wald test uses an asymptotic argument to compare that statistic with a standard normal distribution, while the t-test relies on an exact small-sample argument to compare the test statistic with a t-distribution. While the t-test is not exactly equivalenting to the Wald test, they are asymptotically equivalent.