Chapter 8 Appendix: Data Dictionary

This appendix describes the datasets used in this book.

For each set of data, we provide download buttons so that you can easily access the data in standard .csv (comma separated value) format. This allows you replicate and experiment with the methods developed in the book as well as sharpen your understanding through exercises.

We provide the source of each dataset. We also recommend, for deeper understanding, that you occasionally refer to these original sources to further develop your appreciation of the data underpinning the analytics developed in this book.

8.1 United States Population Mortality Counts

Source: The Human Mortality Database (HMD).

Description: We now bring into consideration mortality experience for populations that had been observed over time, which is available at the Human Mortality Database (HMD) for a wide range of countries. The available data include Exposures by age, sex, and calender year period, i.e. how many people of a given age and sex lived in the country’s population during a given period of time, and corresponding Deaths, i.e. how many of these individuals had died.

The data are available using this download button:

Table 8.1: US Population Mortality Counts First Five Rows

Year_start	Year_end	Age	Female	Male	Total
1935	1939	0	4869267	5057569	9926836
1935	1939	1	4802597	4936238	9738835
1935	1939	2	5119574	5244634	10364208
1935	1939	3	5159494	5287402	10446896
1935	1939	4	5189350	5307754	10497104

Table 8.1: US Population Mortality Counts Last Five Rows

Year_start	Year_end	Age	Female	Male	Total
2010	2014	106	3853.91	415.44	4269.35
2010	2014	107	2031.89	210.41	2242.30
2010	2014	108	1083.62	106.29	1189.91
2010	2014	109	535.32	58.42	593.73
2010	2014	110	576.06	80.03	656.09

Table 8.2: US Population Mortality Counts Summary Statistics

	Year_start	Year_end	Age	Female	Male	Total
	Min. :1935	Min. :1939	Min. : 0	Min. : 56	Min. : 21	Min. : 80
	1st Qu.:1954	1st Qu.:1958	1st Qu.: 27	1st Qu.: 1293833	1st Qu.: 823082	1st Qu.: 2130434
	Median :1972	Median :1976	Median : 55	Median : 5263300	Median : 4850955	Median :10124747
	Mean :1972	Mean :1976	Mean : 55	Mean : 4946072	Mean : 4758380	Mean : 9704453
	3rd Qu.:1991	3rd Qu.:1995	3rd Qu.: 83	3rd Qu.: 8238099	3rd Qu.: 8407376	3rd Qu.:16678945
	Max. :2010	Max. :2014	Max. :110	Max. :11606030	Max. :11674875	Max. :23280905

8.2 Synthetic Insurer Data

Description: We provide survival information for a hypothetical insurance company in SyntheticInsurerData.csv. The company has sold whole life insurance policies, i.e. policies that pay a death benefit upon the policyholder’s death, since 1955. Policyholders have to go through an underwriting examination, and in addition to policyholders’ age, sex (0 for female, 1 for male), smoking status (0 for non-smoker, 1 for smoker), and the month of sale, the company records the applicants body-mass index (BMI) and the systolic blood pressure at the time of underwriting. Finally, for those policyholders with a claim, i.e., for the policyholders that have died, the company records the time of death (relative to the month of underwriting). The data are organized in the order of sales, so that the oldest entries are at the top of the data and the newest entries are at the bottom:

The data are available using this download button:

Table 8.3: Synthetic Insurer First Five Rows

Month_of_Sale	Age	Sex	Smoking	BMI	BloodPressure	Claim	Time_of_death
1	27	0	0	25.8	117	YES	55.63
1	51	1	0	17.6	109	YES	18.53
1	59	1	0	22.5	132	YES	15.88
1	37	1	0	22.9	109	YES	57.40
1	62	0	0	30.9	147	YES	27.83

Table 8.3: Synthetic Insurer Last Five Rows

Month_of_Sale	Age	Sex	Smoking	BMI	BloodPressure	Claim	Time_of_death
780	57	1	1	19.30	118	NO	NA
780	40	0	0	20.10	117	NO	NA
780	27	1	0	20.60	90	NO	NA
780	55	1	1	20.10	118	NO	NA
780	23	1	0	19.03	82	NO	NA

Table 8.4: Synthetic Insurer Summary Statistics

	Month_of_Sale	Age	Sex	Smoking
	Min. : 1	Min. :19	Min. :0.000	Min. :0.000
	1st Qu.:209	1st Qu.:31	1st Qu.:0.000	1st Qu.:0.000
	Median :382	Median :39	Median :1.000	Median :0.000
	Mean :395	Mean :40	Mean :0.699	Mean :0.298
	3rd Qu.:591	3rd Qu.:48	3rd Qu.:1.000	3rd Qu.:1.000
	Max. :780	Max. :65	Max. :1.000	Max. :1.000

	BMI	BloodPressure	Claim	Time_of_death
	Min. :16.1	Min. : 57	NO :101399	Min. : 0
	1st Qu.:19.5	1st Qu.:104	YES: 59382	1st Qu.:18
	Median :21.7	Median :114		Median :28
	Mean :22.8	Mean :115		Mean :28
	3rd Qu.:25.0	3rd Qu.:125		3rd Qu.:39
	Max. :69.6	Max. :208		Max. :64
				NA’s :101399

8.3 Canine Mortality

Source: Canine mortality data are publicly available at Pegram et al. (2021b). See Pegram et al. (2021a) for additional background.

Description: In this dataset, there are 29865 observations used to study euthanasia. Our interest is in survival patterns by age and so we remove records where either the date of birth or death is missing or incorrect (we also removed 17 records with missing sex information); this results in 5933 records for analysis.

The data are available using this download button:

Table 8.5: Canine Mortality First Five Rows

animalid	Sex	Neutered	Breed	CauseDeath	Method.of.death	dateBirth	dateDeath
3534394	Female	Entire	Boston Terrier	Disorder not diagnsosed	Euthanasia	2016-02-02	2016-02-02
11836307	Female	Entire	Bulldog	Behaviour disorder	Euthanasia	2016-09-03	2016-09-03
12090746	Male	Entire	Chinese Shar-Pei	Disorder not diagnsosed	Euthanasia	2016-03-01	2016-03-01
12092145	Female	Neutered	Crossbreed	Collapsed	Euthanasia	2016-01-03	2016-01-03
11739930	Female	Entire	German Shepherd Dog	Disorder not diagnsosed	Euthanasia	2015-04-12	2015-04-12

Table 8.5: Canine Mortality Last Five Rows

animalid	Sex	Neutered	Breed	CauseDeath	Method.of.death	dateBirth	dateDeath
11718193	Female	Entire	Border Terrier	Heart disease	Euthanasia	1998-12-03	2018-01-02
11514456	Male	Entire	Jack Russell Terrier	Musculoskeletal disorder	Euthanasia	1996-10-02	2016-10-02
6916114	Female	Entire	Jack Russell Terrier	Disorder not diagnsosed	Euthanasia	1996-06-09	2016-07-09
11542454	Male	Neutered	Crossbreed	Disorder not diagnsosed	Unassisted	1997-01-09	2017-02-12
3963609	Male	Neutered	Jack Russell Terrier	Heart disease	Euthanasia	1996-01-05	2017-01-09

Table 8.6: Canine Mortality Summary Statistics

	animalid	Sex	Neutered	Breed
	Min. : 881900	Female:2841	Entire :2529	Crossbreed :1259
	1st Qu.: 2401823	Male :3092	Neutered:3404	Staffordshire Bull Terrier: 507
	Median : 6846177			Labrador Retriever : 481
	Mean : 6824982			Jack Russell Terrier : 352
	3rd Qu.:11559402			German Shepherd Dog : 234
	Max. :12493098			Yorkshire Terrier : 192
				(Other) :2908

	CauseDeath	Method.of.death	dateBirth	dateDeath
	Disorder not diagnsosed:1126	Euthanasia:5325	2005-01-03: 28	2016-12-12: 41
	Collapsed : 523	Unassisted: 462	2005-01-05: 26	2016-10-07: 38
	Neoplasia : 522	Unrecorded: 146	2004-01-01: 25	2016-08-09: 37
	Mass : 375		2005-01-06: 25	2016-09-12: 37
	Brain disorder : 350		2003-01-05: 24	2016-11-09: 37
	Behaviour disorder : 341		2003-01-10: 24	2016-04-04: 35
	(Other) :2696		(Other) :5781	(Other) :5708

Show R Code to Pre-Process the Canine Mortality Data

# Read in Revised Data
DogMortA <- read.csv("Data/DogSurvivalData1.csv")
DogMort <- DogMortA[,-1]
DogMort$dateBirth <- as.Date(DogMort$dateBirth, "%Y-%m-%d") 
DogMort$dateDeath <- as.Date(DogMort$dateDeath, "%Y-%m-%d")
DogMort$AgeAtDeath <- (as.numeric(DogMort$dateDeath) - as.numeric(DogMort$dateBirth))/365.25
DogTerr <- subset(DogMort, Breed == "Jack Russell Terrier")
DogGShep <- subset(DogMort, Breed == "German Shepherd Dog")

8.4 Canadian Female Select and Ultimate Mortality Table

Source

• Individual Life Experience Subcommittee, “Construction of CIA9704 Mortality Tables for Canadian Individual Insurance based on data from 1997 to 2004”, Canadian Institute of Actuaries (2010).
• Accessed: October, 2021 from http://www.cia-ica.ca/docs/default-source/2010/210028e.pdf
• Data retrieved from https://mort.soa.org/ (Table 1458)

Select data are available using this download button:

Table 8.7: Canadian Female Select Mortality First Five Rows

Age	Select0	Select1	Select2	Select3	Select4	Select5	Select6
0	0.00035	0.00011	0.00011	0.00010	0.00009	0.00009	0.00009
1	0.00023	0.00011	0.00010	0.00010	0.00009	0.00009	0.00009
2	0.00011	0.00010	0.00010	0.00009	0.00009	0.00009	0.00009
3	0.00010	0.00010	0.00009	0.00009	0.00009	0.00009	0.00009
4	0.00010	0.00009	0.00009	0.00009	0.00009	0.00009	0.00009

Select7	Select8	Select9	Select10	Select11	Select12	Select13	Select14
0.00009	0.00009	0.00009	0.00010	0.00010	0.00011	0.00012	0.00014
0.00009	0.00009	0.00009	0.00010	0.00011	0.00012	0.00013	0.00014
0.00009	0.00009	0.00010	0.00011	0.00012	0.00013	0.00014	0.00016
0.00009	0.00010	0.00011	0.00012	0.00013	0.00014	0.00016	0.00017
0.00010	0.00011	0.00012	0.00013	0.00014	0.00016	0.00017	0.00019

Table 8.7: Canadian Female Select Mortality Last Five Rows

Age	Select0	Select1	Select2	Select3	Select4	Select5	Select6
76	0.00544	0.00819	0.01031	0.01236	0.01440	0.01799	0.02341
77	0.00566	0.00853	0.01073	0.01285	0.01633	0.02153	0.02751
78	0.00588	0.00887	0.01115	0.01457	0.01955	0.02530	0.03235
79	0.00609	0.00920	0.01264	0.01743	0.02298	0.02975	0.03791
80	0.00630	0.01043	0.01513	0.02049	0.02702	0.03486	0.04415

Select7	Select8	Select9	Select10	Select11	Select12	Select13	Select14
0.02963	0.03723	0.04634	0.05706	0.06945	0.08367	0.09994	0.11842
0.03484	0.04363	0.05398	0.06599	0.07978	0.09560	0.11358	0.13176
0.04082	0.05082	0.06243	0.07580	0.09115	0.10864	0.12638	0.14378
0.04755	0.05877	0.07172	0.08661	0.10359	0.12088	0.13790	0.15707
0.05499	0.06751	0.08194	0.09843	0.11526	0.13190	0.15065	0.17193

Ultimate data are available using this download button:

Table 8.8: Canadian Ultimate Mortality First Five Rows

Age	qx
15	0.00015
16	0.00016
17	0.00018
18	0.00019
19	0.00021

Table 8.8: Canadian Ultimate Mortality Last Five Rows

Age	qx
116	0.45
117	0.45
118	0.45
119	0.45
120	1.00

Show R Code to Pre-Process the Canadian Female Select and Ultimate Mortality Data

CanadianSelect <- read.csv("Data/CanadianFemaleSelectRead.csv", stringsAsFactors = FALSE)
CanadianSelect1 <- subset(CanadianSelect, Age >= 50 & Age <= 69)
CanadianSelect2 <- CanadianSelect1[2:6,c(1:6,12,16)]
CanadianSelect3 <- CanadianSelect1[37:41,1:2]
CanadianSelect4 <- cbind(CanadianSelect2,CanadianSelect3[,2],CanadianSelect3[,1])
colnames(CanadianSelect4) <- c("Age", "Select=0","Select=1","Select=2","Select=3","Select=4","Select=10","Select=14", "Ultimate Mortality","Ultimate Age" )
rownames(CanadianSelect4) <- NULL
knitr::kable(CanadianSelect4, align = "r", caption="Select and Ultimate Female Canadian Mortality Rates")

8.5 Korean Mortality by Insured Status

Sources:

• Insured lives and annuitant rates were drawn from a database organized by the Society of Actuaries, https://mort.soa.org/. These represent (beginning of the year) mortality rates (\(q_x\)).
• The general population data are drawn from the Human Mortality Database. General population data are central death rates (\(m_x\)).

Korean Mortality - Insured Lives

The data are available using this download button:

Table 8.9: Korean Female Insured Lives First Five Rows

Age	qx
0	0.00505
1	0.00044
2	0.00034
3	0.00025
4	0.00019

Table 8.9: Korean Female Insured Lives Last Five Rows

Age	qx
108	0.76028
109	0.80509
110	0.84620
111	0.88274
112	1.00000

Korean Mortality - Annuitants

The data are available using this download button:

Table 8.10: Korean Female Annuitant First Five Rows

Age	qx
45	0.00037
46	0.00041
47	0.00045
48	0.00048
49	0.00051

Table 8.10: Korean Female Annuitant Last Five Rows

Age	qx
108	0.66236
109	0.71596
110	0.76430
111	0.80563
112	1.00000

Korean Mortality - Population

The data are available using this download button:

Table 8.11: Korean Female Population First Five Rows

Year	Age	Female	Male	Total
2003	0	0.00485	0.005998	0.00545
2003	1	0.00048	0.000418	0.00045
2003	2	0.00029	0.000409	0.00035
2003	3	0.00029	0.00031	0.00030
2003	4	0.00026	0.000347	0.00031

Table 8.11: Korean Female Population Last Five Rows

Year	Age	Female	Male	Total
2018	106	0.55619	0.667144	0.57057
2018	107	0.61531	0.848961	0.64287
2018	108	0.69828	1.426573	0.76136
2018	109	0.87470	4.285714	1.00386
2018	110	1.80482	.	1.80482

8.6 Mortality by Country

Source: The Human Mortality Database. In addition to classification by country, we also look at experience by sex and age as these distinctions are well known. General population data are central death rates (\(m_x\)).

Population Mortality - Japan

The data are available using this download button:

Table 8.12: Japan Population First Five Rows

Year	Age	Female	Male	Total
1947	0	0.083595	0.095448	0.089645
1947	1	0.035643	0.037017	0.036341
1947	2	0.017271	0.017203	0.017237
1947	3	0.011227	0.01133	0.011279
1947	4	0.007023	0.007468	0.007248

Table 8.12: Japan Population Last Five Rows

Year	Age	Female	Male	Total
2019	106	0.522855	0.69263	0.537623
2019	107	0.534649	0.66628	0.544456
2019	108	0.569069	0.607969	0.571733
2019	109	0.608248	0.806337	0.619736
2019	110	0.630664	0.927907	0.643787

Population Mortality - Poland

The data are available using this download button:

Table 8.13: Poland Population First Five Rows

Year	Age	Female	Male	Total
1958	0	0.065617	0.08371	0.074886
1958	1	0.004736	0.005034	0.004888
1958	2	0.001734	0.002034	0.001888
1958	3	0.001191	0.001463	0.00133
1958	4	0.000853	0.001073	0.000965

Table 8.13: Poland Population Last Five Rows

Year	Age	Female	Male	Total
2019	106	0.423814	0.307903	0.404767
2019	107	0.394572	0.350672	0.387116
2019	108	0.657174	0.760938	0.673882
2019	109	0.529723	0	0.449214
2019	110	1.753104	0	1.517067

Population Mortality - United States

The data are available using this download button:

Table 8.14: USA Population First Five Rows

Year	Age	Female	Male	Total
1933	0	0.05418	0.06818	0.06129
1933	1	0.00887	0.01004	0.00946
1933	2	0.00402	0.00467	0.00435
1933	3	0.00287	0.00333	0.00310
1933	4	0.00223	0.00254	0.00239

Table 8.14: USA Population Last Five Rows

Year	Age	Female	Male	Total
2019	106	0.51709	0.52166	0.51764
2019	107	0.50964	0.58639	0.51840
2019	108	0.63771	0.72411	0.64703
2019	109	0.55038	0.37360	0.53175
2019	110	0.59847	0.50963	0.58832

Show R Code to Pre-Process the Mortality Data by Country

JapanPopFemaleqx  <- as.numeric(JapanPop2019$Female) /(1 + as.numeric(JapanPop2019$Female) /2)
JapanPopMaleqx    <- as.numeric(JapanPop2019$Male)   /(1 + as.numeric(JapanPop2019$Male)   /2)
PolandPopFemaleqx <- as.numeric(PolandPop2019$Female)/(1 + as.numeric(PolandPop2019$Female)/2)
PolandPopMaleqx   <- as.numeric(PolandPop2019$Male)  /(1 + as.numeric(PolandPop2019$Male)  /2)
USAPopFemaleqx    <- as.numeric(USAPop2019$Female)   /(1 + as.numeric(USAPop2019$Female)   /2)
USAPopMaleqx      <- as.numeric(USAPop2019$Male)     /(1 + as.numeric(USAPop2019$Male)     /2)

PolandPopMaleqx[110] <- 1 -> PolandPopMaleqx[111]

IntlMort <- data.frame(cbind(JapanPop2019$Age, JapanPopFemaleqx, JapanPopMaleqx, PolandPopFemaleqx,
                             PolandPopMaleqx, USAPopFemaleqx, USAPopMaleqx))
names(IntlMort) <- c("Age", "qx_Female_Japan", "qx_Male_Japan", "qx_Female_Poland", 
                            "qx_Male_Poland",  "qx_Female_USA", "qx_Male_USA")
#str(IntlMort)

8.7 Disability Income

Source: Zayatz (2015), Tables 14A, 14B, 21A, 21B

Description:

• Entitlement age Entryx denotes age last birthday at entitlement to disability benefits.
• The duration Select.y is measured in years since entitlement.
• Attained age Attainedx is calculated as sum of Entryx and duration.
• The select and ultimate table is read across the row for 0-10 years of entitlement, and down the last (ultimate) column for 10 or more years of entitlement.

Disability Recovery Rates - Male

The data are available using this download button:

Table 8.15: Male Disability Recovery Rates First Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
16	0.00946	0.02160	0.02233	0.01267	0.07644	0.10214
17	0.00826	0.01658	0.01450	0.01257	0.06944	0.08764
18	0.00670	0.01218	0.00836	0.01350	0.05874	0.06920
19	0.00473	0.00892	0.00630	0.01320	0.04634	0.05240
20	0.00380	0.00731	0.00554	0.01249	0.03792	0.04318

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
0.11206	0.07516	0.05687	0.05694	0.04050	26
0.08750	0.06374	0.05063	0.04880	0.03568	27
0.06238	0.05117	0.04317	0.03816	0.03049	28
0.04754	0.04087	0.03595	0.03003	0.02587	29
0.03896	0.03292	0.02919	0.02251	0.02053	30

Table 8.15: Male Disability Recovery Rates Last Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
60	0.00062	0.00063	0.00011	0.00079	0.00162	0.00117
61	0.00048	0.00023	0.00009	0.00062	0.00139	NA
62	0.00026	0.00016	0.00007	0.00026	NA	NA
63	0.00025	0.00024	0.00011	NA	NA	NA
64	0.00026	0.00030	NA	NA	NA	NA

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
NA	NA	NA	NA	NA	70
NA	NA	NA	NA	NA	71
NA	NA	NA	NA	NA	72
NA	NA	NA	NA	NA	73
NA	NA	NA	NA	NA	NA

Disability Recovery Rates - FeMale

The data are available using this download button:

Table 8.16: Female Disability Recovery Rates First Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
16	0.01215	0.01899	0.01408	0.01206	0.04706	0.07218
17	0.00934	0.01440	0.00959	0.01099	0.04697	0.06196
18	0.00609	0.01058	0.00715	0.01107	0.04464	0.04965
19	0.00362	0.00818	0.00568	0.01007	0.03644	0.03809
20	0.00329	0.00661	0.00566	0.00979	0.02933	0.03575

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
0.07609	0.06826	0.07033	0.06010	0.04714	26
0.06484	0.05891	0.06032	0.04966	0.03823	27
0.05337	0.04903	0.04884	0.03708	0.03098	28
0.04048	0.03914	0.03924	0.02870	0.02575	29
0.03482	0.03085	0.03089	0.02314	0.02075	30

Table 8.16: Female Disability Recovery Rates Last Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
61	0.00042	0.00041	0.00014	0.00072	0.00114	NA
62	0.00014	0.00028	0.00014	0.00027	NA	NA
63	0.00020	0.00026	0.00008	NA	NA	NA
64	0.00022	0.00022	NA	NA	NA	NA
65	0.00021	NA	NA	NA	NA	NA

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
NA	NA	NA	NA	NA	71
NA	NA	NA	NA	NA	72
NA	NA	NA	NA	NA	73
NA	NA	NA	NA	NA	74
NA	NA	NA	NA	NA	75

Death and Disability Recovery Rates - Male

The data are available using this download button:

Table 8.17: Male Death and Disability Recovery Rates First Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
16	0.01346	0.02872	0.02758	0.01848	0.08046	0.10458
17	0.01400	0.02485	0.02070	0.01930	0.07425	0.09238
18	0.01401	0.02107	0.01529	0.02065	0.06494	0.07627
19	0.01464	0.01730	0.01359	0.02088	0.05255	0.05890
20	0.01395	0.01596	0.01244	0.02044	0.04439	0.04934

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
0.12126	0.08229	0.06258	0.06316	0.04864	26
0.09451	0.07086	0.05702	0.05431	0.04258	27
0.06708	0.05782	0.04991	0.04365	0.03684	28
0.05211	0.04633	0.04320	0.03540	0.03175	29
0.04340	0.03904	0.03687	0.02785	0.02664	30

Table 8.17: Male Death and Disability Recovery Rates Last Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
61	0.07463	0.04978	0.04177	0.04009	0.04029	0.04387
62	0.08180	0.05426	0.04426	0.04303	0.04556	0.04598
63	0.09568	0.06421	0.05185	0.05028	0.05032	0.05444
64	0.11528	0.07067	0.05558	0.05582	0.05614	0.06220
65	0.12402	0.07477	0.05577	0.06081	0.06072	0.06201

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
0.04736	0.04843	0.05258	0.05482	0.06168	71
0.04972	0.05281	0.05587	0.05792	0.06546	72
0.05605	0.06006	0.06522	0.06520	0.06913	73
0.06177	0.06450	0.07336	0.07356	0.07384	74
0.06473	0.06626	0.08112	0.08198	0.07921	75

Death and Disability Recovery Rates - Female

The data are available using this download button:

Table 8.18: Female Death and Disability Recovery Rates First Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
16	0.01481	0.02314	0.01797	0.01737	0.04979	0.07516
17	0.01449	0.02075	0.01430	0.01620	0.05078	0.06603
18	0.01364	0.01887	0.01258	0.01679	0.04945	0.05459
19	0.01337	0.01690	0.01172	0.01595	0.04237	0.04229
20	0.01250	0.01551	0.01115	0.01620	0.03486	0.04026

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
0.08078	0.07706	0.07673	0.06399	0.05316	26
0.07066	0.06682	0.06595	0.05464	0.04434	27
0.06011	0.05638	0.05342	0.04309	0.03694	28
0.04734	0.04622	0.04415	0.03550	0.03215	29
0.04152	0.03665	0.03668	0.03017	0.02811	30

Table 8.18: Female Death and Disability Recovery Rates Last Five Rows

Entryx	Select.0	Select.1	Select.2	Select.3	Select.4	Select.5
61	0.06242	0.04250	0.03321	0.03149	0.02889	0.03294
62	0.06712	0.04808	0.03830	0.03315	0.03409	0.03497
63	0.07996	0.05552	0.04142	0.04077	0.03742	0.04052
64	0.10067	0.06061	0.04973	0.04358	0.04612	0.04430
65	0.10870	0.06833	0.05638	0.04641	0.05169	0.04504

Select.6	Select.7	Select.8	Select.9	Ultimate	Attainedx
0.03299	0.03625	0.03931	0.04157	0.04377	71
0.03673	0.03888	0.04240	0.04548	0.04678	72
0.04316	0.04318	0.04863	0.04894	0.05029	73
0.04906	0.04904	0.05498	0.05536	0.05343	74
0.05310	0.05493	0.06121	0.06175	0.05798	75

Test a few things

Access from Github instead of OneDrive???

Access button

Then, do a “File==> Save As” to download the data….

References

Pegram, Camilla, Carol Gray, Rowena MA Packer, Ysabelle Richards, David B Church, Dave C Brodbelt, and Dan G O’Neill. 2021a. “Proportion and Risk Factors for Death by Euthanasia in Dogs in the Uk.” Scientific Reports 11 (1): 1–12.

Pegram, Camilla, Carol Gray, Rowena MA Packer, Ysabelle Richards, David B Church, Dave C Brodbelt, and Dan G O’Neill. 2021b. “Proportion and Risk Factors for Death by Euthanasia in Dogs in the Uk– Supporting Data.” https://researchonline.rvc.ac.uk/id/eprint/13486/.

Zayatz, Tim. 2015. “Social Security Disability Insurance Program Worker Experience.” Actuarial Study 123. https://ai.ssa.gov/OACT/NOTES/pdf_studies/study123.pdf.